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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import time |
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model_path = "B:\Arcee\mergekit\merged\Patent" |
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model = AutoModelForCausalLM.from_pretrained(model_path) |
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tokenizer = AutoTokenizer.from_pretrained(model_path) |
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def generate_response(input_text): |
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input_ids = tokenizer(input_text, return_tensors="pt").input_ids |
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start_time = time.time() |
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output = model.generate(input_ids, max_length=256, num_beams=5, temperature=0.7, top_p=0.95, early_stopping=True) |
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end_time = time.time() |
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response = tokenizer.decode(output[0], skip_special_tokens=True) |
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time_taken = end_time - start_time |
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return response, time_taken |
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while True: |
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user_input = input("You: ") |
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if user_input.lower() == 'exit': |
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print("Goodbye!") |
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break |
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response, time_taken = generate_response(user_input) |
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print("Bot:", response) |
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print(f"Time taken: {time_taken:.2f} seconds") |
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