| import gradio as gr | |
| from transformers import AutoModel, AutoTokenizer | |
| # Load the BAGEL model and tokenizer | |
| tokenizer = AutoTokenizer.from_pretrained("ByteDance-Seed/BAGEL-7B-MoT") | |
| model = AutoModel.from_pretrained("ByteDance-Seed/BAGEL-7B-MoT") | |
| # Define a function to generate outputs | |
| def generate(prompt): | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| outputs = model.generate(**inputs) | |
| return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| # Create a Gradio interface | |
| demo = gr.Interface( | |
| fn=generate, # The function to run | |
| inputs="text", # Input type (text box) | |
| outputs="text" # Output type (text box) | |
| ) | |
| # Launch the app | |
| demo.launch() |