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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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"mistralai/Mistral-7B-Instruct-v0.2" |
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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) 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-v0.2'>Mistral-7B-Instruct</a> model. 💬<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>. 📚<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=[["Write a poem with Raskolnikov and Sonia from Crime and Punishment by Dostoyevsky"], ["How does attention mechanism works in a Transformer model?"]] |
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) |
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demo.queue().launch(debug=True) |
