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import gradio as gr |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model = AutoModelForCausalLM.from_pretrained("halil21/lora_model") |
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tokenizer = AutoTokenizer.from_pretrained("halil21/lora_model") |
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def generate_response(user_input): |
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inputs = tokenizer(user_input, return_tensors="pt").input_ids |
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outputs = model.generate(inputs, max_new_tokens=128) |
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response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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return response |
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interface = gr.Interface(fn=generate_response, |
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inputs="text", |
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outputs="text", |
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title="CIED Yönetimi İçin Model", |
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description="Bir klinik durumu değerlendirin ve modelin önerilerini alın.") |
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interface.launch() |
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