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