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import gradio as gr
from huggingface_hub import InferenceClient
client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")
def format_alpaca_prompt(user_input, system_prompt):
"""Formats input in Alpaca/LLaMA style"""
prompt = f"""{system_prompt}
### Instruction:
{user_input}
### Response:
"""
return prompt
def respond(message, history, system_message, max_tokens, temperature, top_p):
formatted_prompt = format_alpaca_prompt(message, system_message)
response = client.text_generation(
formatted_prompt, # β
Pass as a single string
max_new_tokens=max_tokens, # β
Use max_new_tokens, not max_tokens
temperature=temperature,
top_p=top_p,
)
yield response # β
Output the generated response
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
gr.Slider(minimum=1, maximum=250, value=128, step=1, label="Max new tokens"), # β
Keep β€250
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
],
)
if __name__ == "__main__":
demo.launch()
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