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skumar17
searching Neon…
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by
skumar17
2y ago
That’s a good observation. For this project, I found that while the base model could “read” the image, it didn’t really understand how to use it. GRPO allowed it to effectively search the solution space.
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skumar17
2y ago
The attention demo code is in the /attention_demo directory if you want to try it on your own messages too :)
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skumar17
2y ago
Unfortunately it might be a bit challenging as there’s a nontrivial amount of extra computation we do for the viz, but it’s probably possible?
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skumar17
2y ago
Thanks! I really love the visualization too. We have a hosted demo you can try as well! https://huggingface.co/spaces/Groundlight/grpo-vlm-decoder
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Show HN: r1_vlm – Open-Source Framework for Visual Reasoning with GRPO
(github.com)
5 points
by
skumar17
2y ago
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8 comments
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Finding inputs where deep learning models fail
(github.com)
3 points
by
skumar17
2y ago
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1 comments
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by
skumar17
2y ago
Hi there! Last month at NeurIPS (an ML conference), I read an interesting paper "Human Expertise in Algorithmic Prediction" that describes a framework for determining where ML models are outperformed by human experts. I found the
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Building your first computer vision model just got easier
(code.groundlight.ai)
5 points
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skumar17
3y ago
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1 comments
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by
skumar17
3y ago
I just setup this awesome way to easily deploy computer vision models using natural language, check it out: https://code.groundlight.ai/python-sdk/blog/getting-started
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Grime Guardian: Dirty dish detection with declarative computer vision
(code.groundlight.ai)
7 points
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skumar17
3y ago
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1 comments
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by
skumar17
3y ago
I built an application that automatically detects and publicly posts when my coworkers leave dirty dishes in the sink using computer vision. Check it out: https://code.groundlight.ai/python-sdk/blog/grime-guardian
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LoRA from Scratch
(github.com)
4 points
by
skumar17
3y ago
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1 comments
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by
skumar17
3y ago
Hi there! I was interested in learning more about LoRA but I was having a hard time finding a good simple example of implementing LoRA, as most sources are training large models and use a combination of huggingface transformers and the lora