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Runtime error
| import torch | |
| import gradio as gr | |
| from transformers import GPT2Tokenizer, GPT2LMHeadModel | |
| def generate_response(model, tokenizer, prompt, max_length=250): | |
| input_ids = tokenizer.encode(prompt, return_tensors="pt") | |
| # Create the attention mask and pad token id | |
| attention_mask = torch.ones_like(input_ids) | |
| pad_token_id = tokenizer.eos_token_id | |
| output = model.generate( | |
| input_ids, | |
| max_length=max_length, | |
| num_return_sequences=1, | |
| attention_mask=attention_mask, | |
| pad_token_id=pad_token_id | |
| ) | |
| return tokenizer.decode(output[0], skip_special_tokens=True) | |
| model_path = "Tinyants21/Canine_model" | |
| # Load the fine-tuned model and tokenizer | |
| my_chat_model = GPT2LMHeadModel.from_pretrained(model_path) | |
| my_chat_tokenizer = GPT2Tokenizer.from_pretrained(model_path) | |
| def generate_response_gradio(prompt): | |
| response = generate_response(my_chat_model, my_chat_tokenizer, prompt, max_length=250) | |
| return response | |
| title = "Canine Distemper FAQ" | |
| description = "Chatbot that uses a GPT-2 - 775 Million parameter model to answer common questions about canine distemper." | |
| examples = [ | |
| ["What is canine distemper?"], | |
| ["How is canine distemper transmitted?"], | |
| ["Is there a vaccine for canine distemper?"], | |
| ] | |
| inputs = gr.inputs.Textbox(label="Question") | |
| outputs = gr.outputs.Textbox(label="Answer") | |
| gr.Interface(fn=generate_response_gradio, inputs=inputs, outputs=outputs, title=title, description=description, examples=examples).launch() | |