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# Load model directly
from transformers import pipeline
import gradio as gr
import torch
# Check if CUDA is available, otherwise use CPU
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = pipeline("text-generation", model="microsoft/BioGPT-Large", device=device)
def question(message, history):
# Generate the response
response = pipe(message, max_length=200)[0]['generated_text']
return response
#Description in Markdown
description =
program = gr.ChatInterface(question,description=description,title="Microsoft BioGPT Large Chat")
if __name__ == "__main__":
program.launch() |