57 lines
1.9 KiB
Markdown
57 lines
1.9 KiB
Markdown
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---
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license: apache-2.0
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datasets:
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- malhajar/alpaca-gpt4-tr
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language:
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- tr
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- en
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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malhajar/Mistral-7B-Instruct-v0.2-turkish is a finetuned version of [`Mistral-7B-Instruct-v0.2`]( https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) using SFT Training and Freeze method.
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This model can answer information in a chat format as it is finetuned specifically on instructions specifically [`alpaca-gpt4-tr`]( https://huggingface.co/datasets/malhajar/alpaca-gpt4-tr)
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### Model Description
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- **Developed by:** [`Mohamad Alhajar`](https://www.linkedin.com/in/muhammet-alhajar/)
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- **Language(s) (NLP):** Turkish
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- **Finetuned from model:** [`mistralai/Mistral-7B-Instruct-v0.2`](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
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### Prompt Template
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```
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### Instruction:
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<prompt> (without the <>)
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### Response:
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```
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## How to Get Started with the Model
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Use the code sample provided in the original post to interact with the model.
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```python
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from transformers import AutoTokenizer,AutoModelForCausalLM
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model_id = "malhajar/Mistral-7B-Instruct-v0.2-turkish"
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model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
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device_map="auto",
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torch_dtype=torch.float16,
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revision="main")
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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question: "Türkiyenin en büyük şehir nedir?"
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# For generating a response
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prompt = '''
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### Instruction: {question} ### Response:
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'''
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids
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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
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top_p=0.95,trust_remote_code=True,)
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response = tokenizer.decode(output[0])
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print(response)
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```
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