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Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -310,11 +310,11 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
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label="Select Model",
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value="Lumian-VLR-7B-Thinking"
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)
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gr.Markdown("**Model Info 💻** | [Report Bug](https://huggingface.co/spaces/prithivMLmods/Multimodal-VLM-Thinking/discussions)")
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gr.Markdown("> Lumian-VLR-7B-Thinking is a high-fidelity vision-language reasoning model built on Qwen2.5-VL-7B-Instruct,
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gr.Markdown(">
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image_submit.click(
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fn=generate_image,
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inputs=[model_choice, image_query, image_upload, max_new_tokens, temperature, top_p, top_k, repetition_penalty],
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label="Select Model",
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value="Lumian-VLR-7B-Thinking"
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)
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gr.Markdown("**Model Info 💻** | [Report Bug](https://huggingface.co/spaces/prithivMLmods/Multimodal-VLM-Thinking/discussions)")
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gr.Markdown("> Lumian-VLR-7B-Thinking is a high-fidelity vision-language reasoning model built on Qwen2.5-VL-7B-Instruct, designed for fine-grained multimodal understanding, enhancing image captioning, video reasoning, and document comprehension through explicit grounded reasoning. It is trained first via supervised fine-tuning (SFT) on visually-grounded reasoning traces and then further refined using GRPO reinforcement learning to boost reasoning accuracy.")
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gr.Markdown("> LMM-R1-MGT-PerceReason is a vision-language model focused on advanced reasoning using a multimodal tree search approach enabling progressive visual-textual slow thinking, improving complex spatial and logical reasoning without fine-tuning. OLMOCR-7B-0225-preview is a 7B parameter open large model designed for OCR tasks with robust text extraction, especially in complex document layouts. ")
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gr.Markdown("> Typhoon-ocr-3b is a 3B parameter OCR model optimized for efficient and accurate optical character recognition in challenging conditions. DREX-062225-exp is an experimental multimodal model emphasizing strong document reading and extraction capabilities combined with vision-language understanding to support detailed document parsing and reasoning tasks.")
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image_submit.click(
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fn=generate_image,
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inputs=[model_choice, image_query, image_upload, max_new_tokens, temperature, top_p, top_k, repetition_penalty],
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