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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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"meta-llama/Meta-Llama-3-8B-Instruct" |
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) |
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punctuation_marks = [".", "!", "?"] |
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def generate( |
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prompt, history, temperature=0.2, max_new_tokens=256, top_p=0.8, 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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stream = client.text_generation(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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while output and output[-1] not in punctuation_marks: |
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output = output[:-1] |
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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=0.2, |
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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=0.80, |
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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=1.0, |
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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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gr.ChatInterface( |
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fn=generate, |
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chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"), |
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title= "🦙 Have a chat with llama 3 8B 🦙", |
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additional_inputs=additional_inputs, |
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examples=[ |
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["Can you explain briefly to me what is the Python programming language?"], |
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["Write a 100-word article on 'Benefits of Open-Source in AI research'."], |
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], |
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cache_examples=True |
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).launch(show_api=False) |
