alfonsovelp commited on
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8fcea5a
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1 Parent(s): 5e290a2

Update app.py

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  1. app.py +1 -100
app.py CHANGED
@@ -1,102 +1,3 @@
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- from huggingface_hub import InferenceClient
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  import gradio as gr
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- client = InferenceClient(
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- "models/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=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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-
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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>Mistral 7B Instruct<h1><center>")
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- gr.HTML("<h3><center>In this demo, you can chat with <a href='https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1'>Mistral-7B-Instruct</a> model. πŸ’¬<h3><center>")
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- gr.HTML("<h3><center>Learn more about the model <a href='https://huggingface.co/docs/transformers/main/model_doc/mistral'>here</a>. πŸ“š<h3><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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-
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- demo.queue(concurrency_count=75, max_size=100).launch(debug=True)
 
 
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  import gradio as gr
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+ gr.load("mistralai/Mixtral-8x22B-Instruct-v0.1").launch()