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README.md
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tags:
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- translation
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- Bilingual
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---
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# Model
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6487239cca30096ea9f52115/Rsixw_aSB-ytZT7VEQ06c.jpeg" width="500" height="500" alt="Image">
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# Training details
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# Dataset
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tags:
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- translation
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- Bilingual
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datasets:
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- Aarif1430/english-to-hindi
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- Sampuran01/english-hindi-translation
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---
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# Model Description
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The base model [sarvamai/OpenHathi-7B-Hi-v0.1-Base](https://huggingface.co/sarvamai/OpenHathi-7B-Hi-v0.1-Base) was finetuned using [Unsloth](https://github.com/unslothai/unsloth)
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6487239cca30096ea9f52115/Rsixw_aSB-ytZT7VEQ06c.jpeg" width="500" height="500" alt="Image">
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# Steps to try the model :
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## Load the model
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("damerajee/openhathi-h2e-e2h")
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model = AutoModelForCausalLM.from_pretrained("damerajee/openhathi-h2e-e2h")
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```
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## Inference
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```python
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inputs = tokenizer(["[INST]translate this from english to hindi: Be a free thinker and don't accept everything you hear as truth. Be critical and evaluate what you believe in. [/INST]<s> hindi output:"]*1, return_tensors = "pt").to("cuda")
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outputs = model.generate(**inputs, max_new_tokens = 18, use_cache = True)
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tokenizer.batch_decode(outputs)
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```
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```python
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inputs = tokenizer(["[INST]translate this from english to hindi: Be a free thinker and don't accept everything you hear as truth. Be critical and evaluate what you believe in. [/INST]<s> hindi output:"]*1, return_tensors = "pt").to("cuda")
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outputs = model.generate(**inputs, max_new_tokens = 18, use_cache = True)
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tokenizer.batch_decode(outputs)
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```
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# Training details
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* The model was loaded in 4-Bit
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* The target modules include "q_proj", "k_proj", "v_proj", "o_proj"
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* The training took about 2 hours approximately
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* The fine-tuning was done on a free goggle colab with a single t4 GPU (huge thanks to unsloth for this)
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# Dataset
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* The dataset used was the combination of two dataset which gave a total of 1_786_788 rows of hindi text
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* The rows were then pre-process to look something like this :
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```python
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[INST]translate this from english to hindi: When it is said to him: \'Fear Allah\' egotism takes him in his sin. Gehenna (Hell) shall be enough for him. How evil a cradling! [/INST] hindi output: और जब उससे कहा जाता है,
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"अल्लाह से डर", तो अहंकार उसे और गुनाह पर जमा देता है। अतः उसके लिए तो जहन्नम ही काफ़ी है, और वह बहुत-ही बुरी शय्या है! '
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```
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* This was done for both english to hindi and hindi to english hence the name h2e and e2h
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