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import spaces
import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "models/unsloth/Meta-Llama-3.1-8B-bnb-4bit"
@spaces.GPU(duration=180)
def load_model():
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
return model, tokenizer
@spaces.GPU
def generate_text(prompt, model, tokenizer):
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
def gradio_interface():
model, tokenizer = load_model()
def wrapped_generate(prompt):
return generate_text(prompt, model, tokenizer)
iface = gr.Interface(
fn=wrapped_generate,
inputs="text",
outputs="text",
title="Meta-Llama 3.1 8B Text Generation"
)
return iface
if __name__ == "__main__":
demo = gradio_interface()
demo.launch() |