Hugging Face

📢Introducing MeshAnything V2! Surpasses MeshAnything in both performance and efficiency! 💯 Efficiently achieves high-quality, highly controllable 3D Mesh for various 3D asset production pipelines: Image-to-mesh, text-to-mesh, pointcloud-to-mesh, 3DGS-to-mesh & NeRF-to-mesh. MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenization 🤗Demo + details👇 Official Gradio demo on Hugging Face Spaces: https://lnkd.in/g9CpPSHA

Flux.1-Dev like images but in fewer steps. Merging code (very simple), inference code, merged params: https://lnkd.in/gCWrTv3U Enjoy the Monday 🤗

FLUX.1 [schnell] is blowing minds across the SD & MidJourney art community.🤯 All attached images are FLUX-generated by the community and they are unbelievable. For example, some of these images actually look like real photographs! - Try out the new SOTA text-to-Image model today with a Gradio demo on Hugging Face Spaces for free!! - Flux Prompt handling is way better SD3 & Midjourney. - You might find it tough to believe these generated images are from Flux and not MidJourney ! - There are couple examples of artists generating character-sheets with similar looking characters out of the box - Some examples show FLUX being used as a Jewelry Design tool!😍 - FLUX -> More realistic and more detailed images than SD3 Gradio demo on Hugging Face Spaces: https://lnkd.in/dQSXrRpr

Think you know the key to powerful AI? It's not just about fancy models; it's about the data. Voxel51's first-ever Data-Centric AI Competition on Hugging Face Spaces challenges you to prove that data eats models for lunch! The Challenge: Curate, Don't Just Compute Your mission is to create a smaller, more efficient subset of our provided dataset (65,986 images, 43 object classes) that maintains or improves the performance of a YOLOv8m object detection model. This means: ✅ Removing redundant or unhelpful data ✅ Fixing labeling errors ✅ Applying data augmentation 🚫 Don't use external data, add new annotations, or generate synthetic images. 🛠️Your Toolkit • FiftyOne: An open-source tool for dataset curation and analysis (tutorial provided!) • YOLOv8m model: From the Ultralytics Model Zoo • Your ingenuity! Winning Formula We're looking for the sweet spot between dataset size and model performance. Our scoring metric reflects this: Score = (mAP * log(N)) / N Where: mAP: Mean Average Precision on a hidden test set N: Number of images in your curated dataset Prizes Worth Fighting For 🥇 1st Place: $1,000 🥈 2nd Place: Top Tier Community Swag Package 🥉 3rd Place: Mid-Tier Community Swag Package Timeline 🚀 Launch: August 1, 2024 Submissions Open: September 1 - October 27, 2024 🏆 Winners Announced: November 6, 2024 Support System We've got your back! Benefit from: • Workshops: "Getting Started with FiftyOne" (August 21 & September 25) • Check-in/Office Hours: September 6, 13, & 20 Why Participate? • Level up your data curation skills • Make a real-world impact on AI development • Connect with the AI community • Gain recognition for your expertise #data #artificialintelligence #computervision #deeplearning

CatVTON: A simple and most efficient virtual try-on diffusion model🤩 Lightweight (899.06M params only), Parameter-Efficient Training (49.57M parameters trainable), and Inference on less than 8G VRAM for 1024X768 resolution 😍 Gradio App locally: To deploy the Gradio App on your machine, visit CatVTON project, and just run the appdotpy file, and checkpoints will be automatically downloaded from Hugging Face Visit: https://lnkd.in/g-mbWPJY

In case you didn't already know the awesome FLUX model from Black Forest Labs is supported in 🧨 Diffusers. The model has about 12B parameters along with two text encoders. So, it can be burdensome to run. So, we have put together a little gist guiding you on how to run Flux with limited resources. What a model! Check it out here: https://lnkd.in/gr3R9Eza

SF3D is super-fast image to 3D. Generates 3D mesh in 0.5 second🤯 Attached video is not sped up! Demo + Key Details 👇 SF3D: Stable Fast 3D Mesh Reconstruction with UV-unwrapping and Illumination Disentanglement - SF3D is from Stability AI and is based on their previous work TripoSR. - 🤩 Bonus: You can also select an HDR environment to light up your 3D model. - Great work by Mark Boss on the model development and release!🙌 🥳 You can launch a gradio demo in just 3 steps from the SF3D repo: https://lnkd.in/gvpevyez 🤗 OR access the demo on Hugging Face Spaces: https://lnkd.in/gdUFdU5d

Absolutely wild! 🤯 Google DeepMind Gemma 2B  outperforms OpenAI GPT-3.5 on LMSYS Chatbot arena with a score of 1130! 20 months ago, "ChatGPT is a revolution, the most powerful model ever made," and today, you can run a model more preferred than this literally on a toaster!🍞 🚀 Gemma 2B It also ranks higher than: > Microsoft Phi-3 Medium (14B version) > Mistral AI 8x7B Instruct > Mistral AI 7B fine-tunes > Meta Llama 2 70B Test it on Hugging Face: https://lnkd.in/dbn4ZGjg Leaderboard: https://lnkd.in/dA-2CiEi

🚀 Segment Anything Model 2 (SAM 2) is a foundation model from AI at Meta , designed to address promptable visual segmentation in both images and videos. Deploy with Gradio👇 SAM 2 provides strong performance across a wide range of tasks and visual domains. Here is how you can deploy the model with Gradio: ✅ Google Colab: https://lnkd.in/gFjEyNeb ✅ Hugging Face Spaces demo by Piotr Skalski: https://lnkd.in/gwjkC8cs Have fun!!

Trying to catch Andre De Grasse, the reigning 200m Olympic champ from Canada, using AI at Meta's SAM2! How many of you are working on building a demo for video segmentation for SAM2? Let us know how we can help😊