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ehristoforu commited on
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Create app.py

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  1. app.py +99 -0
app.py ADDED
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+ from huggingface_hub import InferenceClient
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+ import gradio as gr
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+
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+ client = InferenceClient(
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+ "mistralai/Mixtral-8x7B-Instruct-v0.1"
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+ )
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+
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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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+
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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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+
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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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+
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+ formatted_prompt = format_prompt(prompt, history)
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+
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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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+
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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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+
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+
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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=512,
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+ minimum=0,
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+ maximum=1048,
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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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+
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+ css = """
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+ #mkd {
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+ height: 500px;
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+ overflow: auto;
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+ border: 1px solid #ccc;
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+ }
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+ """
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+
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+ with gr.Blocks(css=css) as demo:
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+ gr.HTML("<h1><center>Mixtral 70B<h1><center>")
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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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+
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+ demo.queue(concurrency_count=75, max_size=100).launch(debug=True, show_api=False)