Spaces:
Running
Running
placeholders, copy buttons, panel layout, likeable responses
Browse files
app.py
CHANGED
@@ -100,7 +100,7 @@ def respond(
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# -------------------------
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# Create a Chatbot component with a specified height
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chatbot = gr.Chatbot(height=600) # Define the height of the chatbot interface
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print("Chatbot interface created.")
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# Create textboxes and sliders for system prompt, tokens, and other parameters
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],
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fill_height=True, # Allow the chatbot to fill the container height
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chatbot=chatbot, # Chatbot UI component
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theme="Nymbo/Nymbo_Theme", # Theme for the interface
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)
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print("ChatInterface object created.")
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# -----------
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# ADDING THE INFORMATION TAB
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# -----------
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with demo:
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with gr.Tab("Information"):
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with gr.Accordion("Featured Models", open=True):
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gr.HTML(
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"""
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<p><a href="https://huggingface.co/models?inference=warm&pipeline_tag=text-generation&sort=trending">See all available models</a></p>
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<table style="width:100%; text-align:center; margin:auto;">
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<tr>
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<th>Model Name</th>
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<th>Context Length</th>
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<th>Notes</th>
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</tr>
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<tr>
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<td>meta-llama/Llama-3.3-70B-Instruct</td>
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<td>8192</td>
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<td>Most capable model</td>
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</tr>
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<tr>
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<td>meta-llama/Llama-3.2-3B-Instruct</td>
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<td>8192</td>
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<td>Lightweight option</td>
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</tr>
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<tr>
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<td>google/gemma-2-27b-it</td>
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<td>8192</td>
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<td>Google's latest</td>
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</tr>
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<tr>
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<td>mistralai/Mixtral-8x7B-Instruct-v0.1</td>
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<td>32768</td>
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<td>High context length</td>
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</tr>
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</table>
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"""
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)
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with gr.Accordion("Parameters Overview", open=False):
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gr.Markdown(
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"""
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## System Message
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###### This is the initial instruction that guides the model's behavior throughout the conversation. It sets the tone and personality of the assistant.
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## Max Tokens
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###### Controls the maximum length of the generated response. Higher values allow for longer responses but may take more time to generate.
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## Temperature
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###### Controls the randomness of predictions by scaling the logits before applying softmax. Lower values make the model more deterministic.
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## Top-P (Nucleus Sampling)
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###### Controls sampling by selecting from the smallest possible set of tokens whose cumulative probability exceeds the probability p.
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## Frequency Penalty
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###### Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
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## Seed
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###### The seed value provides reproducibility. Using the same seed with the same parameters will produce the same output.
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### Remember, these settings are all about giving you control over the text generation process. Feel free to experiment and see what each one does. Happy generating!
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"""
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)
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# -----------
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# ADDING THE "FEATURED MODELS" ACCORDION
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# -----------
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# -------------------------
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# Create a Chatbot component with a specified height
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chatbot = gr.Chatbot(height=600, show_copy_button=True, placeholder="Select a model and begin chatting", show_copy_all_button=True, likeable=True, layout="panel") # Define the height of the chatbot interface
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print("Chatbot interface created.")
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# Create textboxes and sliders for system prompt, tokens, and other parameters
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],
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fill_height=True, # Allow the chatbot to fill the container height
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chatbot=chatbot, # Chatbot UI component
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textbox=gr.MultimodalTextbox(),
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multimodal=True,
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concurrency_limit=20,
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theme="Nymbo/Nymbo_Theme", # Theme for the interface
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examples=[{"text": "Howdy, partner!",},
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{"text": "What's your model name and who trained you?",},
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{"text": "How many R's are there in the word Strawberry?"},],
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cache_examples=False
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)
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print("ChatInterface object created.")
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# -----------
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# ADDING THE "FEATURED MODELS" ACCORDION
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# -----------
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