Youssef Boulaouane's picture
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Youssef Boulaouane

joseph-bou
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liked a Space 2 days ago
reacted to Xenova's post with πŸ”₯ 7 days ago
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5217
First project of 2025: Vision Transformer Explorer

I built a web app to interactively explore the self-attention maps produced by ViTs. This explains what the model is focusing on when making predictions, and provides insights into its inner workings! 🀯

Try it out yourself! πŸ‘‡
webml-community/attention-visualization

Source code: https://github.com/huggingface/transformers.js-examples/tree/main/attention-visualization
reacted to DawnC's post with ❀️ 7 days ago
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🌟 PawMatchAI: Making Breed Selection More Intuitive! πŸ•
Excited to share the latest update to this AI-powered companion for finding your perfect furry friend! The breed recommendation system just got a visual upgrade to help you make better decisions.

✨ What's New?
Enhanced breed recognition accuracy through strategic model improvements:
- Upgraded to a fine-tuned ConvNeXt architecture for superior feature extraction
- Implemented progressive layer unfreezing during training
- Optimized data augmentation pipeline for better generalization
- Achieved 8% improvement in breed classification accuracy

🎯 Key Features:
- Smart breed recognition powered by AI
- Visual matching scores with intuitive color indicators
- Detailed breed comparisons with interactive tooltips
- Lifestyle-based recommendations tailored to your needs

πŸ’­ Project Vision
Combining my passion for AI and pets, this project represents another step toward my goal of creating meaningful AI applications. Each update aims to make the breed selection process more accessible while improving the underlying technology.

πŸ‘‰ Try it now: DawnC/PawMatchAI

Your likes ❀️ on this space fuel this project's growth!

#AI #MachineLearning #DeepLearning #Pytorch #ComputerVision
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reacted to rwightman's post with πŸ‘ 23 days ago
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I'm currently on a push to expand the scope of image based datasets on the Hub. There's certainly a lot already, but for anyone who's looked closely, there's not a whole lot of standardization. I am to fix that, datasets under the https://huggingface.co/timm and https://huggingface.co/pixparse orgs will serve as canonical examples for various task / modality combinations and be useable without fuss in libraries like timm, OpenCLIP, and hopefully more.

I just uploaded the first multi-label dataset that I'll support with timm scripts soon: timm/plant-pathology-2021

Next up object detection & segmentation! I've got an annotation spec sorted out, a lot of datasets ready to rip, and yeah that means timm support for object detection, eventually segmentation, is finally under development :O
reacted to merve's post with ❀️ about 1 month ago
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This week in open-source AI was insane 🀠 A small recapπŸ•ΊπŸ» merve/dec-6-releases-67545caebe9fc4776faac0a3

Multimodal πŸ–ΌοΈ
> Google shipped a PaliGemma 2, new iteration of PaliGemma with more sizes: 3B, 10B and 28B, with pre-trained and captioning variants πŸ‘
> OpenGVLab released InternVL2, seven new vision LMs in different sizes, with sota checkpoint with MIT license ✨
> Qwen team at Alibaba released the base models of Qwen2VL models with 2B, 7B and 72B ckpts

LLMs πŸ’¬
> Meta released a new iteration of Llama 70B, Llama3.2-70B trained further
> EuroLLM-9B-Instruct is a new multilingual LLM for European languages with Apache 2.0 license πŸ”₯
> Dataset: CohereForAI released GlobalMMLU, multilingual version of MMLU with 42 languages with Apache 2.0 license
> Dataset: QwQ-LongCoT-130K is a new dataset to train reasoning models
> Dataset: FineWeb2 just landed with multilinguality update! πŸ”₯ nearly 8TB pretraining data in many languages!

Image/Video Generation πŸ–ΌοΈ
> Tencent released HunyuanVideo, a new photorealistic video generation model
> OminiControl is a new editing/control framework for image generation models like Flux

Audio πŸ”Š
> Indic-Parler-TTS is a new text2speech model made by community
reacted to rwightman's post with πŸ”₯πŸš€ about 1 month ago
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There's a new timm release, v 1.0.12, with a focus on optimizers. The optimizer factory has been refactored, there's now a timm.optim.list_optimizers() and new way to register optimizers and their attributes. As always you can use an timm optimizer like a torch one, just replace torch.optim with timm.optim

New optimizers include:
* AdafactorBigVision - adfactorbv
* ADOPT - adopt / adoptw (decoupled decay)
* MARS - mars
* LaProp - laprop
* Cautious Optimizers - a modification to all of the above, prefix with c as well as cadamw, cnadamw, csgdw, clamb, crmsproptf

I shared some caution comparisons in this model repo: rwightman/timm-optim-caution

For details, references, see the code: https://github.com/huggingface/pytorch-image-models/tree/main/timm/optim

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