maxiw (Maxi)

posted an update 4 days ago

Post

1508

Exciting to see open-source models thriving in the computer agent space! 🔥
I just built a demo for OS-ATLAS: A Foundation Action Model For Generalist GUI Agents — check it out here: maxiw/OS-ATLAS

This demo predicts bounding boxes based on screenshot + instructions as input.

reacted to cbensimon's post with ❤️ 2 months ago

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4229

Hello everybody,

We've rolled out a major update to ZeroGPU! All the Spaces are now running on it.

Major improvements:

1. GPU cold starts about twice as fast!
2. RAM usage reduced by two-thirds, allowing more effective resource usage, meaning more GPUs for the community!
3. ZeroGPU initializations (coldstarts) can now be tracked and displayed (use progress=gr.Progress(track_tqdm=True))
4. Improved compatibility and PyTorch integration, increasing ZeroGPU compatible spaces without requiring any modifications!

Feel free to answer in the post if you have any questions

🤗 Best regards,
Charles

replied to m-ric's post 2 months ago

HF Space to try it out: maxiw/HTML-to-Markdown

replied to their post 2 months ago

@fridayfairy this is not fine-tuned. It's the base model just prompted to return bounding boxes in a specific format. The Qwen2-VL models must have been pre-trained on detection data.

reacted to rwightman's post with 👍 2 months ago

Post

1267

The timm leaderboard timm/leaderboard has been updated with the ability to select different hardware benchmark sets: RTX4090, RTX3090, two different CPUs along with some NCHW / NHWC layout and torch.compile (dynamo) variations.

Also worth pointing out, there are three rather newish 'test' models that you'll see at the top of any samples/sec comparison:
* test_vit ( timm/test_vit.r160_in1k)
* test_efficientnet ( timm/test_efficientnet.r160_in1k)
* test_byobnet ( timm/test_byobnet.r160_in1k, a mix of resnet, darknet, effnet/regnet like blocks)

They are < 0.5M params, insanely fast and originally intended for unit testing w/ real weights. They have awful ImageNet top-1, it's rare to have anyone bother to train a model this small on ImageNet (the classifier is roughly 30-70% of the param count!). However, they are FAST on very limited hadware and you can fine-tune them well on small data. Could be the model you're looking for?

replied to their post 2 months ago

According to @simonw Gemini might also be able to do this but OpenAI’s GPT-4o and Anthropic’s Claude 3 and Claude 3.5 models can’t.
https://simonwillison.net/2024/Aug/26/gemini-bounding-box-visualization/

posted an update 2 months ago

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2261

The new Qwen-2 VL models seem to perform quite well in object detection. You can prompt them to respond with bounding boxes in a reference frame of 1k x 1k pixels and scale those boxes to the original image size.

You can try it out with my space maxiw/Qwen2-VL-Detection

4 replies

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posted an update 3 months ago

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2267

Just added the newly released xGen-MM v1.5 foundational Large Multimodal Models (LMMs) developed by Salesforce AI Research to my xGen-MM HF Space maxiw/XGen-MM

2 replies

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