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import gradio as gr | |
import os | |
MY_TOKEN = os.getenv('MY_TOKEN') | |
DESCRIPTION = "# Meditron-7B v0.2" | |
from transformers import AutoModelForCausalLM, pipeline, AutoTokenizer | |
model_id = "epfl-llm/meditron-7b" | |
model = AutoModelForCausalLM.from_pretrained(model_id, token=MY_TOKEN) | |
tokenizer = AutoTokenizer.from_pretrained(model_id, token=MY_TOKEN) | |
pp = pipeline("text-generation", model=model, tokenizer=tokenizer) | |
with gr.Blocks(css="style.css") as demo: | |
gr.Markdown(DESCRIPTION) | |
iface = gr.Interface(fn=pp, inputs="text", outputs="text") | |
if __name__ == "__main__": | |
demo.queue(max_size=20).launch() |