Create README.md

README.md

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+---
+datasets:
+- TFLai/Turkish-Alpaca
+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 [`Turkish-Alpaca`]( https://huggingface.co/datasets/TFLai/Turkish-Alpaca) 
+
+### 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)
+```