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import gradio as gr | |
from huggingface_hub import InferenceClient | |
# Initialize the inference client | |
client = InferenceClient("NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO") | |
def generate_response(prompt, max_length=512, temperature=0.7): | |
"""Generate a response from the model and check metadata.""" | |
response = client.text_generation( | |
prompt, | |
max_new_tokens=max_length, | |
temperature=temperature, | |
details=True # This may provide extra model info | |
) | |
print(f"Response Metadata: {response}") # Check if model details are in the response | |
return response["generated_text"] if isinstance(response, dict) else response | |
print(f"Using model: {client.model_id}") | |
# Define the Gradio interface | |
iface = gr.Interface( | |
fn=generate_response, | |
inputs=[ | |
gr.Textbox(label="Input Prompt"), | |
gr.Slider(minimum=50, maximum=1024, value=512, step=50, label="Max Length"), | |
gr.Slider(minimum=0.1, maximum=1.5, value=0.7, step=0.1, label="Temperature"), | |
], | |
outputs=gr.Textbox(label="Generated Response"), | |
title="Nous Hermes 2 Mixtral AI Chatbot", | |
description="An interactive chatbot powered by Nous Hermes 2 Mixtral 8x7B DPO.", | |
) | |
# Launch the app | |
if __name__ == "__main__": | |
iface.launch() | |