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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM
# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("TuringsSolutions/Phi3LawCaseManagement", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("TuringsSolutions/Phi3LawCaseManagement", trust_remote_code=True)
def predict(prompt):
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
return response
# Create Gradio interface
iface = gr.Interface(fn=predict,
inputs="text",
outputs="text",
title="Phi3 Law Case Management Model",
description="A model to assist with law case management.")
# Launch the Gradio app
iface.launch()
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