Push model using huggingface_hub.

README.md

@@ -25,7 +25,7 @@ You can then generate text as follows:
 ```python
 from transformers import pipeline
 
-generator = pipeline("text-generation", model="Setpember//tmp/tmp9xts5xnq/Setpember/Jon_GPT2L_PPO_epi_2")
+generator = pipeline("text-generation", model="Setpember//tmp/tmp49gn1ihq/Setpember/Jon_GPT2L_PPO_epi_2")
 outputs = generator("Hello, my llama is cute")
 ```
 
@@ -35,8 +35,8 @@ If you want to use the model for training or to obtain the outputs from the valu
 from transformers import AutoTokenizer
 from trl import AutoModelForCausalLMWithValueHead
 
-tokenizer = AutoTokenizer.from_pretrained("Setpember//tmp/tmp9xts5xnq/Setpember/Jon_GPT2L_PPO_epi_2")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("Setpember//tmp/tmp9xts5xnq/Setpember/Jon_GPT2L_PPO_epi_2")
+tokenizer = AutoTokenizer.from_pretrained("Setpember//tmp/tmp49gn1ihq/Setpember/Jon_GPT2L_PPO_epi_2")
+model = AutoModelForCausalLMWithValueHead.from_pretrained("Setpember//tmp/tmp49gn1ihq/Setpember/Jon_GPT2L_PPO_epi_2")
 
 inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
 outputs = model(**inputs, labels=inputs["input_ids"])

config.json

@@ -2,7 +2,7 @@
   "accelerator_kwargs": {},
   "adap_kl_ctrl": true,
   "backward_batch_size": 1,
-  "batch_size": 256,
+  "batch_size": 4,
   "cliprange": 0.2,
   "cliprange_value": 0.2,
   "compare_steps": 1,
@@ -11,7 +11,7 @@
   "forward_batch_size": null,
   "gamma": 1,
   "global_backward_batch_size": 1,
-  "global_batch_size": 256,
+  "global_batch_size": 4,
   "gradient_accumulation_steps": 1,
   "horizon": 10000,
   "init_kl_coef": 0.2,
@@ -24,7 +24,7 @@
   "max_grad_norm": null,
   "mini_batch_size": 1,
   "model_name": "Setpember/sft_gpt2_large",
-  "optimize_cuda_cache": null,
+  "optimize_cuda_cache": true,
   "optimize_device_cache": false,
   "ppo_epochs": 4,
   "project_kwargs": {},

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1a93c231b14ff36f0991b1b928d2297aa30bfcac8833ab56483807a88309db53
+oid sha256:f46068fc07ed19236d6cfe10ec53c7d0803f356914542822a2ddbfabbbbf0f89
 size 6652