Spaces:
Running
on
Zero
Running
on
Zero
Add assistant prefix and examples
Browse files
app.py
CHANGED
@@ -21,7 +21,7 @@ EOS_WORDS_IDS = [processor.tokenizer.eos_token_id]
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@spaces.GPU
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def model_inference(
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images, text, decoding_strategy, temperature, max_new_tokens,
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repetition_penalty, top_p
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):
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if text == "" and not images:
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@@ -43,6 +43,9 @@ def model_inference(
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}
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]
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prompt = processor.apply_chat_template(resulting_messages, add_generation_prompt=True)
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inputs = processor(text=prompt, images=[images], return_tensors="pt")
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@@ -81,14 +84,18 @@ with gr.Blocks(fill_height=True) as demo:
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with gr.Column():
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image_input = gr.Image(label="Upload your Image", type="pil")
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query_input = gr.Textbox(label="Prompt")
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submit_btn = gr.Button("Submit")
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output = gr.Textbox(label="Output")
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with gr.Accordion(label="Example Inputs and Advanced Generation Parameters"):
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examples=[
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["example_images/
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["example_images/
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["example_images/
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# Hyper-parameters for generation
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max_new_tokens = gr.Slider(
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@@ -162,13 +169,13 @@ with gr.Blocks(fill_height=True) as demo:
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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, 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
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)
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submit_btn.click(model_inference, inputs = [image_input, query_input, decoding_strategy, temperature,
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max_new_tokens, repetition_penalty, top_p], outputs=output)
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@spaces.GPU
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def model_inference(
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images, text, assistant_prefix, decoding_strategy, temperature, max_new_tokens,
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repetition_penalty, top_p
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):
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if text == "" and not images:
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}
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]
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if assistant_prefix:
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text = f"{assistant_prefix} {text}"
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prompt = processor.apply_chat_template(resulting_messages, add_generation_prompt=True)
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inputs = processor(text=prompt, images=[images], return_tensors="pt")
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with gr.Column():
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image_input = gr.Image(label="Upload your Image", type="pil")
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query_input = gr.Textbox(label="Prompt")
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assistant_prefix = gr.Textbox(label="Assistant Prefix", placeholder="Let's think step by step.")
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submit_btn = gr.Button("Submit")
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output = gr.Textbox(label="Output")
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with gr.Accordion(label="Example Inputs and Advanced Generation Parameters"):
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examples=[
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["example_images/mmmu_example.jpeg", "Let's think step by step.", "Chase wants to buy 4 kilograms of oval beads and 5 kilograms of star-shaped beads. How much will he spend?", "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/travel_tips.jpg", None, "I want to go somewhere similar to the one in the photo. Give me destinations and travel tips.", "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/dummy_pdf.png", None, "How much percent is the order status?", "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/art_critic.png", None, "As an art critic AI assistant, could you describe this painting in details and make a thorough critic?.", "Greedy", 0.4, 512, 1.2, 0.8],
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["example_images/s2w_example.png", None, "What is this UI about?", "Greedy", 0.4, 512, 1.2, 0.8]]
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# Hyper-parameters for generation
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max_new_tokens = gr.Slider(
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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
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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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max_new_tokens, repetition_penalty, top_p], outputs=output)
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