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README.md
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- malhajar/meditron-tr
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language:
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- tr
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- malhajar/meditron-tr
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language:
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- tr
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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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meditron-7b-chat-turkish is a finetuned version on turkish language Alpaca of [`epfl-llm/meditron-7b`](https://huggingface.co/epfl-llm/meditron-7b) using SFT Training.
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This model can answer information about different excplicit ideas in medicine (see [`epfl-llm/meditron-7b`](https://huggingface.co/epfl-llm/meditron-7b) for more info)
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### Model Description
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- **Finetuned by:** [`Mohamad Alhajar`](https://www.linkedin.com/in/muhammet-alhajar/)
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- **Language(s) (NLP):** Turkish,English
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- **Finetuned from model:** [`epfl-llm/meditron-7b`](https://huggingface.co/epfl-llm/meditron-7b)
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### Prompt Template
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```
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### Talimat:
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<prompt> (without the <>)
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### Yanıt:
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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/meditron-7b-chat-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: "Akciğer kanseri nedir?"
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# For generating a response
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prompt = '''
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### Instruction:
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{question}
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### Response:'''
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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,
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top_p=0.95)
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response = tokenizer.decode(output[0])
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print(response)
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```
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