| import gradio as gr |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
|
|
| # Load your model |
| tokenizer = AutoTokenizer.from_pretrained("colorfulscoop/gpt2-small-ja") |
| model = AutoModelForCausalLM.from_pretrained("colorfulscoop/gpt2-small-ja") |
|
|
| # Function to generate AI response |
| def generate(text): |
| inputs = tokenizer(text, return_tensors="pt") |
| outputs = model.generate(**inputs, max_new_tokens=50) |
| return tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]) |
|
|
| # Gradio interface |
| iface = gr.Interface( |
| fn=generate, |
| inputs="text", |
| outputs="text", |
| title="Japanese GPT-2 Chatbot", |
| description="Type a message in Japanese and get a response." |
| ) |
|
|
| iface.launch() |
|
|
