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language: |
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- en |
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- fa |
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## [Model description](#model-description)|[Example output](#example-output)|[Banchmark results](#banchmark-results)|[How to use](#how-to-use)|[Training and finetuning](#training-and-finetuning) | |
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# Model description |
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# Example output: |
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**Example 1:** |
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- Input: "سلام، خوبی؟" |
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- Output: "سلام، خوشحالم که با شما صحبت می کنم. چطور می توانم به شما کمک کنم؟" |
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**Example 2:** |
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- Input: "سلام، خوبی؟" |
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- Output: "سلام، خوشحالم که با شما صحبت می کنم. چطور می توانم به شما کمک کنم؟" |
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# Banchmark results |
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| model | dataset | max_token | prompt | score | |
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|---------------|------------------|-----------|--------|---------| |
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| base-model-7b | ARC-easy-dev | 2 | en-1 | 0.41929 | |
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| base-model-7b | ARC-easy-dev | 80 | en-2 | 0.39122 | |
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| base-model-7b | ARC-easy-dev | 300 | en-1 | 0.34448 | |
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| model | dataset | max_token | prompt | score | |
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|---------------|------------------|-----------|--------|---------| |
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| fa-model-7b | ARC-easy-dev | 80 | en-1 | 0.37894 | |
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| fa-model-7b | ARC-easy-dev | 80 | en-2 | 0.33333 | |
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| fa-model-7b | ARC-easy-dev | 80 | fa-2 | 0.28771 | |
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| fa-model-7b | ARC-easy-dev | 300 | fa-1 | 0.25752 | |
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| fa-model-7b | ARC-easy-dev | 2 | fa-1 | 0.24035 | |
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<br> |
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<br> |
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<br> |
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| model | dataset | max_token | prompt | score | |
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|---------------|--------------------|-----------|--------|---------| |
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| base-model-7b | ARC-challenge-dev | 80 | en-2 | 0.37123 | |
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| base-model-7b | ARC-challenge-dev | 2 | en-2 | 0.36789 | |
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| base-model-7b | ARC-challenge-dev | 2 | en-1 | 0.35451 | |
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| base-model-7b | ARC-challenge-dev | 80 | en-1 | 0.33779 | |
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| model | dataset | max_token | prompt | score | |
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|---------------|--------------------|-----------|--------|---------| |
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| fa-model-7b | ARC-challenge-dev | 2 | en-1 | 0.39298 | |
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| fa-model-7b | ARC-challenge-dev | 80 | en-1 | 0.38421 | |
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| fa-model-7b | ARC-challenge-dev | 2 | en-2 | 0.31929 | |
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| fa-model-7b | ARC-challenge-dev | 80 | en-2 | 0.31754 | |
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# How to use |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("aidal/Persian-Mistral-7B") |
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model = AutoModelForCausalLM.from_pretrained("aidal/Persian-Mistral-7B") |
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input_text = "پایتخت ایران کجاست؟" |
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input_ids = tokenizer(input_text, return_tensors="pt") |
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outputs = model.generate(**input_ids) |
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print(tokenizer.decode(outputs[0])) |
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``` |
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# Training and finetuning |