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osanseviero
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5c0e14a
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Parent(s):
b472032
Create app.py
Browse files
app.py
ADDED
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from huggingface_hub import InferenceClient
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import gradio as gr
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API_URL = "https://api-inference.huggingface.co/models/"
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client = InferenceClient(
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"mistralai/Mistral-7B-Instruct-v0.1"
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)
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def format_prompt(message, history):
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prompt = "<s>"
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for user_prompt, bot_response in history:
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prompt += f"[INST] {user_prompt} [/INST]"
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prompt += f" {bot_response}</s> "
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prompt += f"[INST] {message} [/INST]"
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return prompt
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def generate(
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prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
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):
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temperature = float(temperature)
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if temperature < 1e-2:
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temperature = 1e-2
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top_p = float(top_p)
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generate_kwargs = dict(
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temperature=temperature,
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max_new_tokens=max_new_tokens,
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top_p=top_p,
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repetition_penalty=repetition_penalty,
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do_sample=True,
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seed=42,
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)
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formatted_prompt = format_prompt(prompt, history)
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stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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output += response.token.text
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yield output
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return output
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additional_inputs=[
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gr.Slider(
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label="Temperature",
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value=0.9,
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minimum=0.0,
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maximum=1.0,
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step=0.05,
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interactive=True,
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info="Higher values produce more diverse outputs",
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),
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gr.Slider(
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label="Max new tokens",
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value=256,
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minimum=0,
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maximum=8192,
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step=64,
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interactive=True,
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info="The maximum numbers of new tokens",
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),
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gr.Slider(
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label="Top-p (nucleus sampling)",
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value=0.90,
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minimum=0.0,
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maximum=1,
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step=0.05,
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interactive=True,
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info="Higher values sample more low-probability tokens",
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),
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gr.Slider(
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label="Repetition penalty",
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value=1.2,
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minimum=1.0,
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maximum=2.0,
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step=0.05,
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interactive=True,
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info="Penalize repeated tokens",
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)
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]
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with gr.Blocks() as demo:
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gr.ChatInterface(
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generate,
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additional_inputs=additional_inputs,
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)
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demo.queue().launch(debug=True)
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