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Akhil Theerthala

Akhil-Theerthala
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reacted to merve's post with 🔥 7 days ago
A real-time object detector much faster and accurate than YOLO with Apache 2.0 license just landed to Hugging Face transformers 🔥 D-FINE is the sota real-time object detector that runs on T4 (free Colab) 🤩 > Collection with all checkpoints and demo https://huggingface.co/collections/ustc-community/d-fine-68109b427cbe6ee36b4e7352 Notebooks: > Tracking https://github.com/qubvel/transformers-notebooks/blob/main/notebooks/DFine_tracking.ipynb > Inference https://github.com/qubvel/transformers-notebooks/blob/main/notebooks/DFine_inference.ipynb > Fine-tuning https://github.com/qubvel/transformers-notebooks/blob/main/notebooks/DFine_finetune_on_a_custom_dataset.ipynb h/t @vladislavbro @qubvel-hf @ariG23498 and the authors of the paper 🎩 Regular object detectors attempt to predict bounding boxes in (x, y, w, h) pixel perfect coordinates, which is very rigid and hard to solve 🥲☹️ D-FINE formulates object detection as a distribution for bounding box coordinates, refines them iteratively, and it's more accurate 🤩 Another core idea behind this model is Global Optimal Localization Self-Distillation ⤵️ this model uses final layer's distribution output (sort of like a teacher) to distill to earlier layers to make early layers more performant.
reacted to jsulz's post with 🔥 12 days ago
At https://huggingface.co/xet-team we've been hard at work bringing a new generation of storage to the Hugging Face community, and we’ve crossed some major milestones: 👷 Over 2,000 builders and nearing 100 organizations with access to Xet 🚀 Over 70,000 model and dataset repositories are Xet-backed 🤯 1.4 petabytes managed by Xet As we move repos from LFS to Xet for everyone we onboard, we’re pushing our content-addressed store (CAS). Check out the chart below 👇 of CAS hitting up to 150 Gb/s throughput this past week. All of this growth is helping us build richer insights. We expanded our repo graph, which maps how Xet-backed repositories on the Hub share bytes with each other. Check out the current network in the image below (nodes are repositories, edges are where repos share bytes) and visit the space to see how different versions of Qwen, Llama, and Phi models are grouped together https://huggingface.co/spaces/xet-team/repo-graph Join the waitlist to get access! https://huggingface.co/join/xet
updated a dataset 13 days ago
Akhil-Theerthala/Resume-Analysis-CoTR
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