---
language:
- en
- fa
---

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<h4 align="center">
    <p>
        <b>English</b> |
        <a href="https://huggingface.co/aidal/Persian-Mistral-7B#model-description-1">简体中文</a> |
        <a href="https://github.com/huggingface/transformers/blob/main/README_zh-hant.md">繁體中文</a> |
        <a href="https://github.com/huggingface/transformers/blob/main/README_ko.md">한국어</a> |
        <a href="https://github.com/huggingface/transformers/blob/main/README_es.md">Español</a> |
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        <a href="https://github.com/huggingface/transformers/blob/main/README_ru.md">Русский</a> |
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        <a href="https://github.com/huggingface/transformers/blob/main/README_vi.md">Tiếng Việt</a> |
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</h4>
## [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:

**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 |

<br>
<br>
<br>

| 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 |

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# 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