| import gradio as gr | |
| from transformers import pipeline | |
| generator = pipeline("text-generation", model="AdaptLLM/law-LLM") | |
| def generate(input): | |
| return generator( | |
| input, | |
| max_length=10, | |
| num_return_sequences=1, | |
| ) | |
| iface = gr.Interface(fn=generate, inputs="text", outputs="text") | |
| iface.launch() | |