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--- |
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tags: |
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- autotrain |
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- text-generation |
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- meta-llama |
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- meta-llama/Llama-2-7b-hf |
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inference: true |
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widget: |
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- text: > |
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instruction: "If you are a doctor, please answer the medical questions based |
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on the patient's description." |
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input: "Hi, I had a subarachnoid bleed and coiling of brain aneurysm last |
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year. I am having some major bilateral temple pain along with numbness that |
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comes and goes in my left arm/hand/fingers. I have had headaches since the |
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aneurysm, but this is different. Also, my moods have been horrible for the |
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past few weeks." |
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response: '' |
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library_name: peft |
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--- |
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```python |
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!huggingface-cli login |
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_| _| _| _| _|_|_| _|_|_| _|_|_| _| _| _|_|_| _|_|_|_| _|_| _|_|_| _|_|_|_| |
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_| _| _| _| _| _| _| _|_| _| _| _| _| _| _| _| |
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_|_|_|_| _| _| _| _|_| _| _|_| _| _| _| _| _| _|_| _|_|_| _|_|_|_| _| _|_|_| |
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_| _| _| _| _| _| _| _| _| _| _|_| _| _| _| _| _| _| _| |
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_| _| _|_| _|_|_| _|_|_| _|_|_| _| _| _|_|_| _| _| _| _|_|_| _|_|_|_| |
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To login, `huggingface_hub` requires a token generated from https://huggingface.co./settings/tokens . |
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Token: <your-hf-access-token> |
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``` |
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```python |
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from peft import PeftModel, PeftConfig |
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from transformers import AutoModelForCausalLM |
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from transformers import AutoTokenizer |
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import torch |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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config = PeftConfig.from_pretrained("Ashishkr/llama2_medical_consultation") |
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model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") |
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model = PeftModel.from_pretrained(model, "Ashishkr/llama2_medical_consultation").to(device) |
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tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b-hf") |
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``` |
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```python |
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def llama_generate( |
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model: AutoModelForCausalLM, |
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tokenizer: AutoTokenizer, |
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prompt: str, |
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max_new_tokens: int = 128, |
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temperature: float = 0.92): |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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inputs = tokenizer( |
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[prompt], |
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return_tensors="pt", |
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return_token_type_ids=False, |
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).to( |
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device |
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) |
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with torch.autocast("cuda", dtype=torch.bfloat16): |
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response = model.generate( |
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**inputs, |
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max_new_tokens=max_new_tokens, |
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temperature=temperature, |
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return_dict_in_generate=True, |
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eos_token_id=tokenizer.eos_token_id, |
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pad_token_id=tokenizer.pad_token_id, |
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) |
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decoded_output = tokenizer.decode( |
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response["sequences"][0], |
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skip_special_tokens=True, |
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) |
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return decoded_output[len(prompt) :] |
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prompt = """ |
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instruction: "If you are a doctor, please answer the medical questions based on the patient's description." \n |
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input: "Hi, I had a subarachnoid bleed and coiling of brain aneurysm last year. |
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I am having some major bilateral temple pain along with numbness that comes and |
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goes in my left arm/hand/fingers. I have had headaches since the aneurysm, |
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but this is different. Also, my moods have been horrible for the past few weeks.\n |
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response: """ |
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response = llama_generate( |
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model, |
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tokenizer, |
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prompt, |
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max_new_tokens=100, |
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temperature=0.92, |
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) |
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print(response) |
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``` |
