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de7ad40
1
Parent(s):
7dc26fc
Update app.py
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app.py
CHANGED
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@@ -1,100 +1,4 @@
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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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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=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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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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with gr.Blocks(css=css, theme="NoCrypt/[email protected]") as demo:
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gr.HTML("<h1><center><a href='https://huggingface.co/openchat/openchat_3.5'>OpenChat</a> Demo Space<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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examples=[["What is the secret to life?"], ["Write me a recipe for pancakes."]]
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)
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demo.queue(max_size=100).launch(debug=True)
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import gradio as gr
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# Lade das Chat-Modell und starte die Benutzeroberfläche mit angepassten Breiten- und Höhenparametern.
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gr.Interface.load("models/openchat/openchat_3.5").launch(width=1000, height=500)
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