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Runtime error
Runtime error
Commit
Β·
504ac73
1
Parent(s):
a558847
Bring up advanced settings
Browse files- app_dialogue.py +69 -71
app_dialogue.py
CHANGED
@@ -376,80 +376,78 @@ with gr.Blocks(title="AI Dad Jokes", theme=gr.themes.Base()) as demo:
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clear_btn = gr.ClearButton([textbox, imagebox, chatbot], value="π§Ή Clear")
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regenerate_btn = gr.Button(value="π Regenerate", visible=True)
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upload_btn = gr.UploadButton("π Upload image", file_types=["image"],visible=False)
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with gr.Column():
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chatbot.render()
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with gr.Row():
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with gr.Accordion("Advanced settings", open=False, visible=True) as parameter_row:
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system_prompt = gr.Textbox(
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value=SYSTEM_PROMPT,
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visible=False,
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lines=20,
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max_lines=50,
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interactive=True,
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)
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max_new_tokens = gr.Slider(
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minimum=8,
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maximum=256,
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value=64,
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step=1,
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interactive=True,
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label="Maximum number of new tokens to generate",
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)
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repetition_penalty = gr.Slider(
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minimum=0.0,
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maximum=5.0,
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value=1.2,
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step=0.01,
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interactive=True,
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label="Repetition penalty",
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info="1.0 is equivalent to no penalty",
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)
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decoding_strategy = gr.Radio(
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[
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"Greedy",
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"Top P Sampling",
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],
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value="Top P Sampling",
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label="Decoding strategy",
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interactive=True,
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info="Higher values is equivalent to sampling more low-probability tokens.",
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)
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temperature = gr.Slider(
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minimum=0.0,
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maximum=5.0,
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value=0.6,
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step=0.1,
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interactive=True,
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visible=True,
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label="Sampling temperature",
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info="Higher values will produce more diverse outputs.",
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)
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decoding_strategy.change(
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fn=lambda selection: gr.Slider.update(
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visible=(
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selection in ["contrastive_sampling", "beam_sampling", "Top P Sampling", "sampling_top_k"]
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)
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),
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inputs=decoding_strategy,
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outputs=temperature,
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)
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top_p = gr.Slider(
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minimum=0.01,
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maximum=0.99,
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value=0.8,
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step=0.01,
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interactive=True,
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visible=True,
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label="Top P",
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info="Higher values is equivalent to sampling more low-probability tokens.",
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)
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decoding_strategy.change(
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fn=lambda selection: gr.Slider.update(visible=(selection in ["Top P Sampling"])),
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inputs=decoding_strategy,
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outputs=top_p,
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)
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def model_inference(
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model_selector,
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system_prompt,
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clear_btn = gr.ClearButton([textbox, imagebox, chatbot], value="π§Ή Clear")
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regenerate_btn = gr.Button(value="π Regenerate", visible=True)
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upload_btn = gr.UploadButton("π Upload image", file_types=["image"],visible=False)
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with gr.Accordion("Advanced settings", open=False, visible=True) as parameter_row:
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system_prompt = gr.Textbox(
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value=SYSTEM_PROMPT,
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visible=False,
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lines=20,
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max_lines=50,
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interactive=True,
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)
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max_new_tokens = gr.Slider(
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minimum=8,
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maximum=256,
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value=64,
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step=1,
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interactive=True,
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label="Maximum number of new tokens to generate",
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)
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repetition_penalty = gr.Slider(
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minimum=0.0,
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maximum=5.0,
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value=1.2,
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step=0.01,
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interactive=True,
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label="Repetition penalty",
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info="1.0 is equivalent to no penalty",
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)
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decoding_strategy = gr.Radio(
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[
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"Greedy",
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"Top P Sampling",
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],
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value="Top P Sampling",
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label="Decoding strategy",
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interactive=True,
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info="Higher values is equivalent to sampling more low-probability tokens.",
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)
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temperature = gr.Slider(
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minimum=0.0,
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maximum=5.0,
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value=0.6,
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step=0.1,
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interactive=True,
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visible=True,
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label="Sampling temperature",
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info="Higher values will produce more diverse outputs.",
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)
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decoding_strategy.change(
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fn=lambda selection: gr.Slider.update(
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visible=(
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selection in ["contrastive_sampling", "beam_sampling", "Top P Sampling", "sampling_top_k"]
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)
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),
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inputs=decoding_strategy,
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outputs=temperature,
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)
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top_p = gr.Slider(
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minimum=0.01,
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maximum=0.99,
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value=0.8,
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step=0.01,
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interactive=True,
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visible=True,
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label="Top P",
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info="Higher values is equivalent to sampling more low-probability tokens.",
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)
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decoding_strategy.change(
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fn=lambda selection: gr.Slider.update(visible=(selection in ["Top P Sampling"])),
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inputs=decoding_strategy,
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outputs=top_p,
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)
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with gr.Column():
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chatbot.render()
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def model_inference(
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model_selector,
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system_prompt,
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