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Running on Zero
Running on Zero
Update app.py
Browse files
app.py
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@@ -74,7 +74,7 @@ def model_inference(
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return generated_texts[0]
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with gr.Blocks() as demo:
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gr.Markdown("## SmolVLM: Small yet Mighty 💫")
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gr.Markdown("Play with [HuggingFaceTB/SmolVLM-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM-Instruct) in this demo. To get started, upload an image and text or try one of the examples.")
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with gr.Column():
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@@ -87,8 +87,21 @@ with gr.Blocks() as demo:
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with gr.Accordion(label="Advanced Generation Parameters", open=False):
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# Hyper-parameters for generation
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max_new_tokens = gr.Slider(
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minimum=8,
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@@ -159,20 +172,7 @@ with gr.Blocks() as demo:
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inputs=decoding_strategy,
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outputs=top_p,
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)
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["example_images/rococo.jpg", "What art era is this?", None, "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/examples_wat_arun.jpg", "Give me travel tips for the area around this monument.", None, "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/examples_invoice.png", "What is the due date and the invoice date?", None, "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/s2w_example.png", "What is this UI about?", None, "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/examples_weather_events.png", "Where do the severe droughts happen according to this diagram?", None, "Greedy", 0.4, 512, 1.2, 0.8],
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]
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gr.Examples(
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examples = examples,
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inputs=[image_input, query_input, assistant_prefix, decoding_strategy, temperature,
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max_new_tokens, repetition_penalty, top_p],
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outputs=output,
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fn=model_inference, cache_examples=False
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)
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submit_btn.click(model_inference, inputs = [image_input, query_input, assistant_prefix, decoding_strategy, temperature,
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return generated_texts[0]
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with gr.Blocks(fill_height=True) as demo:
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gr.Markdown("## SmolVLM: Small yet Mighty 💫")
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gr.Markdown("Play with [HuggingFaceTB/SmolVLM-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM-Instruct) in this demo. To get started, upload an image and text or try one of the examples.")
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with gr.Column():
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with gr.Accordion(label="Examples and Advanced Generation Parameters", open=False):
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examples=[
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["example_images/rococo.jpg", "What art era is this?", None, "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/examples_wat_arun.jpg", "Give me travel tips for the area around this monument.", None, "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/examples_invoice.png", "What is the due date and the invoice date?", None, "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/s2w_example.png", "What is this UI about?", None, "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/examples_weather_events.png", "Where do the severe droughts happen according to this diagram?", None, "Greedy", 0.4, 512, 1.2, 0.8],
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]
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gr.Examples(
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examples = examples,
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inputs=[image_input, query_input, assistant_prefix, decoding_strategy, temperature,
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max_new_tokens, repetition_penalty, top_p],
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outputs=output,
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fn=model_inference, cache_examples=False
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)
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# Hyper-parameters for generation
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max_new_tokens = gr.Slider(
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minimum=8,
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inputs=decoding_strategy,
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outputs=top_p,
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)
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submit_btn.click(model_inference, inputs = [image_input, query_input, assistant_prefix, decoding_strategy, temperature,
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