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Showing posts older than #2238 · Back to latest

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Post #2237 110
Hugging Face (Twitter)

RT @evalstate: Open Weights & Open Source v Claude Code. How does [Toad's] fractal on the title page work? Speeded up 4x. Mixture of zai-org/GLM-4.7 and openai/gpt-oss via Hugging Face Inference providers. Join Toad Explorers and get $20 of inference provider credits
Post #2236 104
Hugging Face (Twitter)

RT @staghado: 🚀 LightOnOCR-2-1B 🦉 is out, a major update to LightOnOCR.
1B parameters, end-to-end multilingual OCR, and it beats models 9× larger on OlmOCR-Bench while being much faster.
PDF/page in, clean ordered Markdown out, with optional image localization (bbox variants).
Post #2233 96
Hugging Face (Twitter)

RT @RisingSayak: In case anyone missed -- new models were shipped in Diffusers this week.

1️⃣ Flux.2 Klein - significantly consumer-friendlier than Flux.2

2️⃣ GLM Image - AR + Diffusion Decoder

Check'em out!
Post #2228 63
Hugging Face (Twitter)

RT @HuggingPapers: Meta just released Action100M on Hugging Face

A massive video dataset with 100M+ hierarchical action annotations.
Every video includes tree-of-captions with action labels, brief and detailed summaries.
Post #2222 44
Hugging Face (Twitter)

RT @bfl_ml: Introducing FLUX.2 [klein]. Blazing fast. Beautiful.

Generate stunning images in under a second while maintaining exceptional quality.

Great for fast editing, changing styles, and developing ideas from 0 → 1.

Available via API, or run it locally - Klein 4B under Apache 2.0, Klein 9B as open weights.

Try it for free in our demo app (link in the thread).
Post #2221 30
Hugging Face (Twitter)

RT @ben_burtenshaw: Finally! We (the community + @OpenAIDevs + @huggingface ) bring you an open standard for inference. It's called 'Open Responses' it's based on Responses and it's perfect for agent workloads. Fewer special cases, more consistency, faster shipping. Excited for what this unlocks.

Below is a deep dive blog post, we’ll look at how Open Responses works and why the open source community should use Open Responses.
Post #2219 36
‌Hugging Face (Twitter)

RT @GoogleDeepMind: Built on Gemma 3, TranslateGemma was trained on data generated by Gemini – effectively transferring its intelligence into a smaller package.

This means developers can build low-latency translation tools that run entirely on-device.

Try it now on @huggingface and @Kaggle ↓ goo.gle/4sHFo0V
Google TranslateGemma: A new suite of open translation models TranslateGemma is a new family of open translation models built on Gemma 3.
Post #2218 40
Hugging Face (Twitter)

RT @GoogleDeepMind: We’re releasing TranslateGemma, a new family of open translation models with support for 55 languages. 🌐

Available in 4B, 12B, and 27B parameter sizes – they’re designed for efficiency without sacrificing quality.
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