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english_only/tok_english_only/tok_files_check/tokenizer_0.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaa
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer0/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaa \
+ --output-prefix $FINAL_DIR/tokenizer0/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_1.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalab
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer1/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalab \
+ --output-prefix $FINAL_DIR/tokenizer1/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_10.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalak
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer10/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalak \
+ --output-prefix $FINAL_DIR/tokenizer10/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_11.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalal
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer11/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalal \
+ --output-prefix $FINAL_DIR/tokenizer11/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_12.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalam
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer12/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalam \
+ --output-prefix $FINAL_DIR/tokenizer12/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_13.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalan
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer13/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalan \
+ --output-prefix $FINAL_DIR/tokenizer13/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_14.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalao
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer14/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalao \
+ --output-prefix $FINAL_DIR/tokenizer14/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_15.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalap
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer15/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalap \
+ --output-prefix $FINAL_DIR/tokenizer15/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_16.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaq
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer16/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaq \
+ --output-prefix $FINAL_DIR/tokenizer16/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_17.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalar
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer17/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalar \
+ --output-prefix $FINAL_DIR/tokenizer17/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_18.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalas
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer18/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalas \
+ --output-prefix $FINAL_DIR/tokenizer18/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_19.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalat
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer19/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalat \
+ --output-prefix $FINAL_DIR/tokenizer19/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_2.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalac
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer2/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalac \
+ --output-prefix $FINAL_DIR/tokenizer2/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_20.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalau
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer20/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalau \
+ --output-prefix $FINAL_DIR/tokenizer20/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_21.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalav
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer21/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalav \
+ --output-prefix $FINAL_DIR/tokenizer21/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_22.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaw
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer22/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaw \
+ --output-prefix $FINAL_DIR/tokenizer22/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_23.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalax
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer23/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalax \
+ --output-prefix $FINAL_DIR/tokenizer23/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_24.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalay
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer24/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalay \
+ --output-prefix $FINAL_DIR/tokenizer24/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_25.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaz
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer25/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaz \
+ --output-prefix $FINAL_DIR/tokenizer25/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_26.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalba
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer26/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalba \
+ --output-prefix $FINAL_DIR/tokenizer26/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_27.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbb
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer27/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbb \
+ --output-prefix $FINAL_DIR/tokenizer27/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_28.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbc
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer28/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbc \
+ --output-prefix $FINAL_DIR/tokenizer28/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_29.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbd
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer29/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbd \
+ --output-prefix $FINAL_DIR/tokenizer29/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_3.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalad
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer3/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalad \
+ --output-prefix $FINAL_DIR/tokenizer3/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_30.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbe
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer30/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbe \
+ --output-prefix $FINAL_DIR/tokenizer30/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_31.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbf
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer31/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbf \
+ --output-prefix $FINAL_DIR/tokenizer31/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_32.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbg
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer32/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbg \
+ --output-prefix $FINAL_DIR/tokenizer32/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_33.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbh
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer33/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbh \
+ --output-prefix $FINAL_DIR/tokenizer33/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_34.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbi
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer34/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbi \
+ --output-prefix $FINAL_DIR/tokenizer34/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_35.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbj
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer35/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbj \
+ --output-prefix $FINAL_DIR/tokenizer35/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_36.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbk
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer36/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbk \
+ --output-prefix $FINAL_DIR/tokenizer36/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_37.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbl
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer37/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbl \
+ --output-prefix $FINAL_DIR/tokenizer37/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_38.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbm
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer38/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbm \
+ --output-prefix $FINAL_DIR/tokenizer38/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_39.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbn
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer39/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalbn \
+ --output-prefix $FINAL_DIR/tokenizer39/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_4.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalae
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer4/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalae \
+ --output-prefix $FINAL_DIR/tokenizer4/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_5.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaf
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer5/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaf \
+ --output-prefix $FINAL_DIR/tokenizer5/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_6.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalag
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer6/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalag \
+ --output-prefix $FINAL_DIR/tokenizer6/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_7.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalah
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer7/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalah \
+ --output-prefix $FINAL_DIR/tokenizer7/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_8.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalai
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer8/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalai \
+ --output-prefix $FINAL_DIR/tokenizer8/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

english_only/tok_english_only/tok_files_check/tokenizer_9.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+set -m
+sed -i -e "s/raw_content/text/g" /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaj
+echo "above deepspeed$"
+FINAL_DIR=/mnt/weka/peacock/idc/hineng/english_only_check/
+#TOKENIZER=facebook/nllb-200-distilled-600M
+#TOKENIZER_TYPE=HuggingFaceTokenizer
+TOKENIZER_PATH=/mnt/weka/peacock/tokenization/trained-tokenizer/encode_32k/
+TOKENIZER=$TOKENIZER_PATH/en_code_32kspm_tokenizer.model
+VOCAB_FILE=$TOKENIZER_PATH/en_code_32kspm_tokenizer.vocab
+TOKENIZER_TYPE=SentencePieceTokenizer
+mkdir -p $FINAL_DIR/tokenizer9/
+cd /mnt/weka/peacock/experiments/llama/Megatron-DeepSpeed
+echo "inside deepspeed"
+pwd
+python3 tools/preprocess_data.py \
+ --input /mnt/weka/peacock/idc/datasets/english_only//tok_english_only/split//finalaj \
+ --output-prefix $FINAL_DIR/tokenizer9/ \
+  --tokenizer-model $TOKENIZER \
+  --vocab-file $VOCAB_FILE  \
+    --dataset-impl mmap --tokenizer-type $TOKENIZER_TYPE\
+    --append-eod --workers 8 # --partitions 16 #--chunk-size 50   
+
+  # --merge-file $MERGES_FILE \
+

hn_eng_bn/tok_en-bn-hn/tok_jobs_9/tokenizer_800.yaml

@@ -0,0 +1,104 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-en-bn-hn-800
+  namespace: peacock
+  labels:
+    app: peacock-tokenizer-en-bn-hn-800
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 1
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-tokenizer-en-bn-hn-800-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  
+                  export SYNAPSE_VERSION="1.15.1";
+                  export WORKER_DIR="/mnt/weka/peacock/experiments/llama";
+
+                  export MEGATRON_SETUP_CMD="$WORKER_DIR/launch/setup.sh"
+                  export TOKENIZER_CMD=/mnt/weka/peacock/idc/datasets/hn_eng_bn/tok_en-bn-hn/tok_files/tokenizer_800.sh
+                  HOSTSFILE=$OMPI_MCA_orte_default_hostfile;
+                  echo "HOSTSFILE=$HOSTSFILE";
+                  MASTER_ADDR="$(head -n 1 $HOSTSFILE | sed -n s/[[:space:]]slots.*//p)";
+                  NUM_NODES=$(wc -l < $HOSTSFILE);
+                  CARDS_PER_NODE=8;
+                  N_CARDS=$((NUM_NODES*CARDS_PER_NODE));
+                  echo "MPI_ROOT=$MPI_ROOT";
+                  echo "N_CARDS=$N_CARDS";
+                  echo "MASTER_ADDR=$MASTER_ADDR";
+                  sleep 20;
+
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $MEGATRON_SETUP_CMD;
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+                    
+                   
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          tolerations:
+            - key: "habana.ai/gaudi"
+              operator: "Exists"
+              effect: "NoSchedule"
+            - key: "k8s/namespace"
+              operator: "Equal"
+              value: "peacock"
+              effect: "NoSchedule"
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-llama-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock

hn_eng_bn/tok_en-bn-hn/tok_jobs_9/tokenizer_801.yaml

@@ -0,0 +1,104 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-en-bn-hn-801
+  namespace: peacock
+  labels:
+    app: peacock-tokenizer-en-bn-hn-801
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 1
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-tokenizer-en-bn-hn-801-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  
+                  export SYNAPSE_VERSION="1.15.1";
+                  export WORKER_DIR="/mnt/weka/peacock/experiments/llama";
+
+                  export MEGATRON_SETUP_CMD="$WORKER_DIR/launch/setup.sh"
+                  export TOKENIZER_CMD=/mnt/weka/peacock/idc/datasets/hn_eng_bn/tok_en-bn-hn/tok_files/tokenizer_801.sh
+                  HOSTSFILE=$OMPI_MCA_orte_default_hostfile;
+                  echo "HOSTSFILE=$HOSTSFILE";
+                  MASTER_ADDR="$(head -n 1 $HOSTSFILE | sed -n s/[[:space:]]slots.*//p)";
+                  NUM_NODES=$(wc -l < $HOSTSFILE);
+                  CARDS_PER_NODE=8;
+                  N_CARDS=$((NUM_NODES*CARDS_PER_NODE));
+                  echo "MPI_ROOT=$MPI_ROOT";
+                  echo "N_CARDS=$N_CARDS";
+                  echo "MASTER_ADDR=$MASTER_ADDR";
+                  sleep 20;
+
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $MEGATRON_SETUP_CMD;
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+                    
+                   
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          tolerations:
+            - key: "habana.ai/gaudi"
+              operator: "Exists"
+              effect: "NoSchedule"
+            - key: "k8s/namespace"
+              operator: "Equal"
+              value: "peacock"
+              effect: "NoSchedule"
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-llama-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock

hn_eng_bn/tok_en-bn-hn/tok_jobs_9/tokenizer_802.yaml

@@ -0,0 +1,104 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-en-bn-hn-802
+  namespace: peacock
+  labels:
+    app: peacock-tokenizer-en-bn-hn-802
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 1
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-tokenizer-en-bn-hn-802-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  
+                  export SYNAPSE_VERSION="1.15.1";
+                  export WORKER_DIR="/mnt/weka/peacock/experiments/llama";
+
+                  export MEGATRON_SETUP_CMD="$WORKER_DIR/launch/setup.sh"
+                  export TOKENIZER_CMD=/mnt/weka/peacock/idc/datasets/hn_eng_bn/tok_en-bn-hn/tok_files/tokenizer_802.sh
+                  HOSTSFILE=$OMPI_MCA_orte_default_hostfile;
+                  echo "HOSTSFILE=$HOSTSFILE";
+                  MASTER_ADDR="$(head -n 1 $HOSTSFILE | sed -n s/[[:space:]]slots.*//p)";
+                  NUM_NODES=$(wc -l < $HOSTSFILE);
+                  CARDS_PER_NODE=8;
+                  N_CARDS=$((NUM_NODES*CARDS_PER_NODE));
+                  echo "MPI_ROOT=$MPI_ROOT";
+                  echo "N_CARDS=$N_CARDS";
+                  echo "MASTER_ADDR=$MASTER_ADDR";
+                  sleep 20;
+
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $MEGATRON_SETUP_CMD;
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+                    
+                   
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          tolerations:
+            - key: "habana.ai/gaudi"
+              operator: "Exists"
+              effect: "NoSchedule"
+            - key: "k8s/namespace"
+              operator: "Equal"
+              value: "peacock"
+              effect: "NoSchedule"
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-llama-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock

hn_eng_bn/tok_en-bn-hn/tok_jobs_9/tokenizer_803.yaml

@@ -0,0 +1,104 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-en-bn-hn-803
+  namespace: peacock
+  labels:
+    app: peacock-tokenizer-en-bn-hn-803
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 1
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-tokenizer-en-bn-hn-803-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  
+                  export SYNAPSE_VERSION="1.15.1";
+                  export WORKER_DIR="/mnt/weka/peacock/experiments/llama";
+
+                  export MEGATRON_SETUP_CMD="$WORKER_DIR/launch/setup.sh"
+                  export TOKENIZER_CMD=/mnt/weka/peacock/idc/datasets/hn_eng_bn/tok_en-bn-hn/tok_files/tokenizer_803.sh
+                  HOSTSFILE=$OMPI_MCA_orte_default_hostfile;
+                  echo "HOSTSFILE=$HOSTSFILE";
+                  MASTER_ADDR="$(head -n 1 $HOSTSFILE | sed -n s/[[:space:]]slots.*//p)";
+                  NUM_NODES=$(wc -l < $HOSTSFILE);
+                  CARDS_PER_NODE=8;
+                  N_CARDS=$((NUM_NODES*CARDS_PER_NODE));
+                  echo "MPI_ROOT=$MPI_ROOT";
+                  echo "N_CARDS=$N_CARDS";
+                  echo "MASTER_ADDR=$MASTER_ADDR";
+                  sleep 20;
+
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $MEGATRON_SETUP_CMD;
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+                    
+                   
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          tolerations:
+            - key: "habana.ai/gaudi"
+              operator: "Exists"
+              effect: "NoSchedule"
+            - key: "k8s/namespace"
+              operator: "Equal"
+              value: "peacock"
+              effect: "NoSchedule"
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-llama-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock

hn_eng_bn/tok_en-bn-hn/tok_jobs_9/tokenizer_805.yaml

@@ -0,0 +1,104 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-en-bn-hn-805
+  namespace: peacock
+  labels:
+    app: peacock-tokenizer-en-bn-hn-805
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 1
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-tokenizer-en-bn-hn-805-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  
+                  export SYNAPSE_VERSION="1.15.1";
+                  export WORKER_DIR="/mnt/weka/peacock/experiments/llama";
+
+                  export MEGATRON_SETUP_CMD="$WORKER_DIR/launch/setup.sh"
+                  export TOKENIZER_CMD=/mnt/weka/peacock/idc/datasets/hn_eng_bn/tok_en-bn-hn/tok_files/tokenizer_805.sh
+                  HOSTSFILE=$OMPI_MCA_orte_default_hostfile;
+                  echo "HOSTSFILE=$HOSTSFILE";
+                  MASTER_ADDR="$(head -n 1 $HOSTSFILE | sed -n s/[[:space:]]slots.*//p)";
+                  NUM_NODES=$(wc -l < $HOSTSFILE);
+                  CARDS_PER_NODE=8;
+                  N_CARDS=$((NUM_NODES*CARDS_PER_NODE));
+                  echo "MPI_ROOT=$MPI_ROOT";
+                  echo "N_CARDS=$N_CARDS";
+                  echo "MASTER_ADDR=$MASTER_ADDR";
+                  sleep 20;
+
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $MEGATRON_SETUP_CMD;
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+                    
+                   
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          tolerations:
+            - key: "habana.ai/gaudi"
+              operator: "Exists"
+              effect: "NoSchedule"
+            - key: "k8s/namespace"
+              operator: "Equal"
+              value: "peacock"
+              effect: "NoSchedule"
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-llama-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock

hn_eng_bn/tok_en-bn-hn/tok_jobs_9/tokenizer_806.yaml

@@ -0,0 +1,104 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-en-bn-hn-806
+  namespace: peacock
+  labels:
+    app: peacock-tokenizer-en-bn-hn-806
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 1
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-tokenizer-en-bn-hn-806-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  
+                  export SYNAPSE_VERSION="1.15.1";
+                  export WORKER_DIR="/mnt/weka/peacock/experiments/llama";
+
+                  export MEGATRON_SETUP_CMD="$WORKER_DIR/launch/setup.sh"
+                  export TOKENIZER_CMD=/mnt/weka/peacock/idc/datasets/hn_eng_bn/tok_en-bn-hn/tok_files/tokenizer_806.sh
+                  HOSTSFILE=$OMPI_MCA_orte_default_hostfile;
+                  echo "HOSTSFILE=$HOSTSFILE";
+                  MASTER_ADDR="$(head -n 1 $HOSTSFILE | sed -n s/[[:space:]]slots.*//p)";
+                  NUM_NODES=$(wc -l < $HOSTSFILE);
+                  CARDS_PER_NODE=8;
+                  N_CARDS=$((NUM_NODES*CARDS_PER_NODE));
+                  echo "MPI_ROOT=$MPI_ROOT";
+                  echo "N_CARDS=$N_CARDS";
+                  echo "MASTER_ADDR=$MASTER_ADDR";
+                  sleep 20;
+
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $MEGATRON_SETUP_CMD;
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+                    
+                   
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          tolerations:
+            - key: "habana.ai/gaudi"
+              operator: "Exists"
+              effect: "NoSchedule"
+            - key: "k8s/namespace"
+              operator: "Equal"
+              value: "peacock"
+              effect: "NoSchedule"
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-llama-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock

hn_eng_bn/tok_en-bn-hn/tok_jobs_9/tokenizer_807.yaml

@@ -0,0 +1,104 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-en-bn-hn-807
+  namespace: peacock
+  labels:
+    app: peacock-tokenizer-en-bn-hn-807
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 1
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-tokenizer-en-bn-hn-807-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  
+                  export SYNAPSE_VERSION="1.15.1";
+                  export WORKER_DIR="/mnt/weka/peacock/experiments/llama";
+
+                  export MEGATRON_SETUP_CMD="$WORKER_DIR/launch/setup.sh"
+                  export TOKENIZER_CMD=/mnt/weka/peacock/idc/datasets/hn_eng_bn/tok_en-bn-hn/tok_files/tokenizer_807.sh
+                  HOSTSFILE=$OMPI_MCA_orte_default_hostfile;
+                  echo "HOSTSFILE=$HOSTSFILE";
+                  MASTER_ADDR="$(head -n 1 $HOSTSFILE | sed -n s/[[:space:]]slots.*//p)";
+                  NUM_NODES=$(wc -l < $HOSTSFILE);
+                  CARDS_PER_NODE=8;
+                  N_CARDS=$((NUM_NODES*CARDS_PER_NODE));
+                  echo "MPI_ROOT=$MPI_ROOT";
+                  echo "N_CARDS=$N_CARDS";
+                  echo "MASTER_ADDR=$MASTER_ADDR";
+                  sleep 20;
+
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $MEGATRON_SETUP_CMD;
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+                    
+                   
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          tolerations:
+            - key: "habana.ai/gaudi"
+              operator: "Exists"
+              effect: "NoSchedule"
+            - key: "k8s/namespace"
+              operator: "Equal"
+              value: "peacock"
+              effect: "NoSchedule"
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-llama-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock

hn_eng_bn/tok_en-bn-hn/tok_jobs_9/tokenizer_808.yaml

@@ -0,0 +1,104 @@
+apiVersion: kubeflow.org/v2beta1
+kind: MPIJob
+metadata:
+  name: peacock-tokenizer-en-bn-hn-808
+  namespace: peacock
+  labels:
+    app: peacock-tokenizer-en-bn-hn-808
+spec:
+  slotsPerWorker: 8
+  runPolicy:
+    backoffLimit: 1
+    cleanPodPolicy: Running
+  mpiReplicaSpecs:
+    Launcher:
+      replicas: 1
+      template:
+        spec:
+          hostIPC: true
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-tokenizer-en-bn-hn-808-launcher
+              imagePullPolicy: IfNotPresent
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock
+              command: ["/bin/bash", "-c"]
+              args:
+                - >-
+                  
+                  export SYNAPSE_VERSION="1.15.1";
+                  export WORKER_DIR="/mnt/weka/peacock/experiments/llama";
+
+                  export MEGATRON_SETUP_CMD="$WORKER_DIR/launch/setup.sh"
+                  export TOKENIZER_CMD=/mnt/weka/peacock/idc/datasets/hn_eng_bn/tok_en-bn-hn/tok_files/tokenizer_808.sh
+                  HOSTSFILE=$OMPI_MCA_orte_default_hostfile;
+                  echo "HOSTSFILE=$HOSTSFILE";
+                  MASTER_ADDR="$(head -n 1 $HOSTSFILE | sed -n s/[[:space:]]slots.*//p)";
+                  NUM_NODES=$(wc -l < $HOSTSFILE);
+                  CARDS_PER_NODE=8;
+                  N_CARDS=$((NUM_NODES*CARDS_PER_NODE));
+                  echo "MPI_ROOT=$MPI_ROOT";
+                  echo "N_CARDS=$N_CARDS";
+                  echo "MASTER_ADDR=$MASTER_ADDR";
+                  sleep 20;
+
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $MEGATRON_SETUP_CMD;
+
+                  mpirun -np $N_CARDS  -npernode 8 \
+                    --tag-output \
+                    --allow-run-as-root \
+                    --prefix $MPI_ROOT \
+                    -x WORKER_DIR=$WORKER_DIR \
+                    -x SYNAPSE_VERSION=$SYNAPSE_VERSION $TOKENIZER_CMD;
+                    
+                   
+    Worker:
+      replicas: 1
+      template:
+        spec:
+          volumes:
+            - name: work-dir
+              persistentVolumeClaim:
+                claimName: peacock-fs-pvc
+          tolerations:
+            - key: "habana.ai/gaudi"
+              operator: "Exists"
+              effect: "NoSchedule"
+            - key: "k8s/namespace"
+              operator: "Equal"
+              value: "peacock"
+              effect: "NoSchedule"
+          hostIPC: true
+          containers:
+            - image: vault.habana.ai/gaudi-docker/1.15.1/ubuntu22.04/habanalabs/pytorch-installer-2.2.0:latest
+              name: peacock-llama-worker
+              imagePullPolicy: IfNotPresent
+              securityContext:
+                capabilities:
+                  add:
+                    - SYSLOG
+              resources:
+                limits:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+                requests:
+                  habana.ai/gaudi: 8
+                  hugepages-2Mi: 300Gi
+                  memory: 700Gi
+                  cpu: 150
+              volumeMounts:
+                - name: work-dir
+                  mountPath: /mnt/weka/peacock