README.md

---
datasets:
- malhajar/alpaca-gpt4-tr
language:
- tr
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->
malhajar/Mixtral-8x7B-v0.1-turkish is a finetuned version of Mixtral-8x7B-v0.1 using SFT Training.
This model can answer information in turkish language as it is finetuned on a turkish dataset specifically [`alpaca-gpt4-tr`]( https://huggingface.co/datasets/malhajar/alpaca-gpt4-tr) 

### Model Description

- **Developed by:** [`Mohamad Alhajar`](https://www.linkedin.com/in/muhammet-alhajar/) 
- **Language(s) (NLP):** Turkish
- **Finetuned from model:** [`mistralai/Mixtral-8x7B-v0.1`](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1)

### Prompt Template
```
### Instruction:

<prompt> (without the <>)

### Response:
```
## How to Get Started with the Model

Use the code sample provided in the original post to interact with the model.
```python
from transformers import AutoTokenizer,AutoModelForCausalLM
 
model_id = "malhajar/Mixtral-8x7B-v0.1-turkish"
model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
                                             device_map="auto",
                                             torch_dtype=torch.float16,
                                             revision="main")

tokenizer = AutoTokenizer.from_pretrained(model_id)

question: "Türkiyenin en büyük şehir nedir?"
# For generating a response
prompt = f'''
### Instruction:  {question} ### Response:
'''
input_ids = tokenizer(prompt, return_tensors="pt").input_ids
output = model.generate(inputs=input_ids,max_new_tokens=512,pad_token_id=tokenizer.eos_token_id,top_k=50, do_sample=True,repetition_penalty=1.3
        top_p=0.95,trust_remote_code=True,)
response = tokenizer.decode(output[0])

print(response)
```