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```python |
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from transformers import GPT2Tokenizer, GPT2LMHeadModel |
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def generate_response(input_text): |
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inputs = tokenizer(input_text, return_tensors="pt") |
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output_sequences = model.generate( |
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input_ids=inputs['input_ids'], |
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attention_mask=inputs['attention_mask'], |
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max_length=100, # Adjusted max_length |
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temperature=0.3, |
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top_k=40, |
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top_p=0.85, |
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num_return_sequences=1, |
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no_repeat_ngram_size=2, |
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pad_token_id=tokenizer.eos_token_id, |
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early_stopping=True, |
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do_sample=True, |
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use_cache=True, |
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) |
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full_generated_text = tokenizer.decode(output_sequences[0], skip_special_tokens=True) |
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bot_response_start = full_generated_text.find('[Bot]') + len('[Bot]') |
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bot_response = full_generated_text[bot_response_start:] |
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last_period_index = bot_response.rfind('.') |
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if last_period_index != -1: |
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bot_response = bot_response[:last_period_index + 1] |
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return bot_response.strip() |
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model_name = 'KhantKyaw/Chat_GPT-2' |
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tokenizer = GPT2Tokenizer.from_pretrained(model_name) |
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model = GPT2LMHeadModel.from_pretrained(model_name) |
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response = generate_response(user_input) |
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print("Chatbot:", response) |
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``` |