Hugging Face

‌Hugging Face (Twitter) RT @googleaidevs: 🗣 Introducing TranslateGemma, our new collection of open translation models built on Gemma 3. The model is available in 4B, 12B, and 27B parameter sizes, and furthers communication across languages, no matter what device you own.

Hugging Face (Twitter) RT @wjb_mattingly: Introducing FreeFlow! Want a free open-source way to annotate data and train Yolo models? FreeFlow is a flask app that lets you annotate data, train Yolo models locally or via @HuggingFace jobs, and then use those models in-the-loop to annotate. Special thanks to @vanstriendaniel for testing and improving it! Good for projects with private data. Full disclosure. This is vibe coded.

Hugging Face (Twitter) RT @ClementDelangue: Was fun to meet @thdxr@opencode today. Let’s go open-source coding agents!

Hugging Face (Twitter) RT @Meituan_LongCat: 🚀 Introducing LongCat-Flash-Thinking-2601 — A version built for deep and general agentic thinking. ✨ Highlights: 🤖 Top Tier Agent Capabilities 🔹 Performance: Top tier benchmark results (TIR / Agentic Search / Agentic Tool Use) ; superb generalization ability, outperforming Claude in complex, random tasks 🔹 Env Scaling: Multiple automaticly constructed high-quality environments; dense dependency graph 🔹 Multi-Env RL: Extended DORA (our RL infra), supporting large-scale multi-environment agentic training 🛡️ Real-World Robustness 🔹 Performance: Solid performance in messy, uncertain scenarios (Vita-Noise & Tau^2-Noise) 🔹 Noise Analysis: Systematically analyzed real-world noise in agentic scenarios 🔹 Curriculum RL: Increasing noise type & intensity while training 🎯 Heavy Thinking Mode ​🔹 Parallel Thinking: Expands breadth via multiple independent reasoning tracks 🔹 Iterative Summarization: Enhances depth by using a summary... Перейти на оригинальный пост

Hugging Face (Twitter) RT @ClementDelangue: What is needed for startups and medium-size tech companies to contribute to open science and open-source AI more? When thinking about open-source, people usually think about big tech or academia but in my opinion, startups and medium-sized tech companies could be massive contributors and benefit a ton from sharing AI models, datasets, research,... (in terms of visibility, hiring, ability to transition into AI,...). We're seeing that a lot in China and looks like we might start to see it in the US too as showed by the fact that the two trending models on @huggingface have been from these types of orgs (@fal and @Lightricks). Also interesting that @Airbnb@bchesky hired @Ahmad_Al_Dahle (former Llama lead) maybe to do more of that?

Hugging Face (Twitter) RT @RisingSayak: If you're fed up babysitting popular kernel builds for hours and are on the verge of giving it up 🤗 1. Thoroughly tested 2. `torch.compile` compatibility where relevant 3. Version control 4. Version bound 5. More time to build AGI Let's go!

Hugging Face (Twitter) RT @ltx_model: 1,000,000 Hugging Face downloads, and counting! LTX-2 grew the way we believe products should: in the open, with the community, through real-world use. Grateful for everyone who helped get us here and excited for what’s next. Download and try it for yourself here: https://huggingface.co/Lightricks/LTX-2

‌Hugging Face (Twitter) RT @HuggingPapers: Qwen just released DeepPlanning on Hugging Face a challenging benchmark for evaluating long-horizon agentic planning features multi-day travel planning and multi-product shopping tasks with verifiable constraints https://huggingface.co/datasets/Qwen/DeepPlanning

Hugging Face (Twitter) RT @sundarpichai: MedGemma 1.5 is a major upgrade to our open models for healthcare developers. The new 4B model enables developers to build applications that natively interpret full 3D scans (CTs, MRIs) with high efficiency - a first, we believe, for an open medical generalist model. MedGemma 1.5 also pairs well with MedASR, our speech-to-text model fine-tuned for highly accurate medical dictation. Developers can now use these multimodal capabilities to build medical apps that reach patients in more places.

Hugging Face (Twitter) RT @Xianbao_QIAN: Z.ai keeps delivering! Buy their stocks to support them on the HK market :) Their wonderful team just dropped GLM-image, a cutting edge image generation model with hybrid autoregressive + diffusion decoder architecture: - The AR part is on top of GLM-4-9B-0414 with an extended vocabulary to incorporate visual tokens. - The diffusion latent decoder is a single stream DiT arch with 7B parameters The model was posted trained on RL with GRPO. Thanks to its architecture, the model can support image generation with dense text / knowledge. It also supports very powerful image editing. How much closer can we get to Nano Bananas? Try the model on @huggingface with the inference provider widget.

‌Hugging Face (Twitter) RT @googleaidevs: Announcing MedGemma 1.5 🩺 This updated open model from @GoogleResearch is small enough to run offline, improves performance on medical imaging use cases, and enhances core capabilities for text, medical records and 2D images. https://research.google/blog/next-generation-medical-image-interpretation-with-medgemma-15-and-medical-speech-to-text-with-medasr/

‌Hugging Face (Twitter) RT @googleaidevs: Access MedGemma variants on Vertex AI and @huggingface today.