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Showing posts older than #1995 · Back to latest

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Post #1994 12
Hugging Face (Twitter)

RT @0xDevShah: Don’t think people fully realize this yet, but we beat China and companies with billions in funding at Voice AI.

Our model is faster, cheaper, and higher quality than anything else on the market. And MIT licensed. It effectively ends the intelligence deflation problem in this space.

You can fine-tune the model, build entirely new voices on top of it, add watermarking, and still run inference at a sustainable cost. https://twitter.com/0xDevShah/status/2000631462786400718#m
Post #1990 16
Hugging Face (Twitter)

RT @AdinaYakup: New model from @Meituan_LongCat 🚀

LongCat-Video-Avatar🔥 Audio driven character animation with text, image, and video inputs, all in one!

✨ MIT license
✨ Audio > talking video (single & multi-person)
✨ Natural motion and lip sync
✨ Fewer repeats, stable identity
✨ Available on @huggingface
Post #1986 8
Hugging Face (Twitter)

RT @allen_ai: Last year Molmo set SOTA on image benchmarks + pioneered image pointing. Millions of downloads later, Molmo 2 brings Molmo’s grounded multimodal capabilities to video 🎥—and leads many open models on challenging industry video benchmarks. 🧵
Post #1985 9
Hugging Face (Twitter)

RT @ben_burtenshaw: Fine-tune Nemotron 3 Nano in TRL with coding agents like claude code, colab, locally or on the hub.

To fine tune, pick one of these tools:
- Combine HF skills with a coding agent like claude code.
- Use this colab notebook.
- Train it on HF jobs using the Hugging Face hub
- If you can, run this script on your own setup with uv

This should get anyone started with fine tuning, and this is the perfect model to start with.
Post #1984 12
Hugging Face (Twitter)

RT @_weiping: 🚀 Introducing Nemotron-Cascade! 🚀

We’re thrilled to release Nemotron-Cascade, a family of general-purpose reasoning models trained with cascaded, domain-wise reinforcement learning (Cascade RL), delivering best-in-class performance across a wide range of benchmarks.

💻 Coding powerhouse
After RL, our 14B model:
• Surpasses DeepSeek-R1-0528 (671B) on LiveCodeBench v5/v6/Pro.
• Achieves silver-medal performance at IOI 2025 🥈.
• Reaches a 43.1% pass@1 on SWE-Bench Verified, and 53.8% with test-time scaling.

🧠 What is Cascade RL?
Instead of mixing heterogeneous prompts across domains, Cascade RL trains sequentially, domain by domain, which reduces engineering complexity, mitigates heterogeneous verification latencies, and enables domain-specific curricula and tailored hyperparameter tuning.

✨ Key insight
Using RLHF for alignment as a pre-step dramatically boosts complex reasoning—far beyond preference optimization. Subsequent...

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Post #1983 11
Hugging Face (Twitter)

RT @DylanTFWang: 🎮Get a first look at Tencent HY World 1.5 (WorldPlay)! 🎮
Our newest world model with real-time interaction and long-term memory.

It’s going *open-source* tomorrow.
Post #1981 17
Hugging Face (Twitter)

RT @allen_ai: 🗓️ Tue Dec 16, 1–2pm PT: AMA with researchers + engineers from our Olmo & Molmo teams, hosted by r/LocalLLaMA (@LocalLLaMAsub).
💬 Ask your questions now—we’ll start answering when the AMA begins!
Post #1976 16
Hugging Face (Twitter)

RT @donvito: No Gemma 4 yet so I went through Google’s @huggingface

Discovered this, wow

MedGemma is a collection of Gemma 3 variants that are trained for performance on medical text and image comprehension

Developers can use MedGemma to accelerate building healthcare-based AI applications
Post #1974 12
Hugging Face (Twitter)

RT @allen_ai: Introducing Bolmo, a new family of byte-level language models built by "byteifying" our open Olmo 3—and to our knowledge, the first fully open byte-level LM to match or surpass SOTA subword models across a wide range of tasks. 🧵
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