--- language: - en - fa --- ![image/webp](https://i.postimg.cc/VN4F7WRC/Untitled-design-modified.png) ## [Model description](#model-description)|[Example output](#example-output)|[Banchmark results](#banchmark-results)|[How to use](#how-to-use)|[Training and finetuning](#training-and-finetuning) | ---- # Model description ---- # Example output: **Example 1:** - Input: "سلام، خوبی؟" - Output: "سلام، خوشحالم که با شما صحبت می کنم. چطور می توانم به شما کمک کنم؟" **Example 2:** - Input: "سلام، خوبی؟" - Output: "سلام، خوشحالم که با شما صحبت می کنم. چطور می توانم به شما کمک کنم؟" ---- # Banchmark results | model | dataset | max_token | prompt | score | |---------------|------------------|-----------|--------|---------| | base-model-7b | ARC-easy-dev | 2 | en-1 | 0.41929 | | base-model-7b | ARC-easy-dev | 80 | en-2 | 0.39122 | | base-model-7b | ARC-easy-dev | 300 | en-1 | 0.34448 | | model | dataset | max_token | prompt | score | |---------------|------------------|-----------|--------|---------| | fa-model-7b | ARC-easy-dev | 80 | en-1 | 0.37894 | | fa-model-7b | ARC-easy-dev | 80 | en-2 | 0.33333 | | fa-model-7b | ARC-easy-dev | 80 | fa-2 | 0.28771 | | fa-model-7b | ARC-easy-dev | 300 | fa-1 | 0.25752 | | fa-model-7b | ARC-easy-dev | 2 | fa-1 | 0.24035 |


| model | dataset | max_token | prompt | score | |---------------|--------------------|-----------|--------|---------| | base-model-7b | ARC-challenge-dev | 80 | en-2 | 0.37123 | | base-model-7b | ARC-challenge-dev | 2 | en-2 | 0.36789 | | base-model-7b | ARC-challenge-dev | 2 | en-1 | 0.35451 | | base-model-7b | ARC-challenge-dev | 80 | en-1 | 0.33779 | | model | dataset | max_token | prompt | score | |---------------|--------------------|-----------|--------|---------| | fa-model-7b | ARC-challenge-dev | 2 | en-1 | 0.39298 | | fa-model-7b | ARC-challenge-dev | 80 | en-1 | 0.38421 | | fa-model-7b | ARC-challenge-dev | 2 | en-2 | 0.31929 | | fa-model-7b | ARC-challenge-dev | 80 | en-2 | 0.31754 | ---- # How to use ```python from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("aidal/Persian-Mistral-7B") model = AutoModelForCausalLM.from_pretrained("aidal/Persian-Mistral-7B") input_text = "پایتخت ایران کجاست؟" input_ids = tokenizer(input_text, return_tensors="pt") outputs = model.generate(**input_ids) print(tokenizer.decode(outputs[0])) ``` ---- # Training and finetuning