Omnilingual ASR: Advancing Automatic Speech Recognition for 1,600+ Languages
We’re introducing Meta Omnilingual Automatic Speech Recognition, a suite of models providing automatic speech recognition capabilities for over 1,600 languages.
We’re introducing Meta Omnilingual Automatic Speech Recognition, a suite of models providing automatic speech recognition capabilities for over 1,600 languages.
At PyTorch Conference 2025 in San Francisco, we unveiled five new projects spanning kernel languages, distributed systems, reinforcement learning, agentic frameworks, and edge AI deployment.
Instituto PROA, a nonprofit organization in Brazil, has transformed its job preparation process for young candidates by leveraging Llama and Oracle Cloud Infrastructure.
DINOv3 scales self-supervised learning for images to create universal vision backbones that achieve absolute state-of-the-art performance across diverse domains, including web and satellite imagery.
Using DINOv2, the team at NASA's Jet Propulsion Laboratory built a convenient robot operating system interface for robotic tasks.
WRI and the Bezos Earth Fund used DINOv3 to develop an algorithm to accurately count individual trees from drone and satellite imagery.
Brazil, the biotech company Biofy Technologies has developed a groundbreaking platform using Llama that reduces diagnostic time for antibiotic resistance from five days to less than…
Upwork, one of the world’s largest work marketplaces, is using Llama to power Uma, its mindful AI, to help freelancers land jobs faster and more confidently.
We're joining forces with Amazon Web Services to announce a new program that will provide resources and support to 30 promising startups in the U.S. that…
Llama 4 Support ( https://www.llama.com )
Llama 4 Inference Fast & Affordable – Now Live on GroqCloud
What's Changed fix: do not use python_tag when encoding non-code_interpreter tool_calls by @ehhuang in #283 fix: tool_call was not encoded by @ehhuang in #284 Full Changelog:…
Setting the record straight regarding Yi-34B and Llama 2.
Llama is Meta's open-weight LLM family — Llama 2, 3, 3.1, 3.2 (vision), 3.3, 4. The most-downloaded open-weight family on Hugging Face, the foundation of nearly every open-source LLM derivative (Vicuna, Mistral-derived models, fine-tunes for code, languages, domains).
Owner: Meta. We have 37 stories indexed for this model, auto-tagged from titles across every tracked source — official announcements, papers, GitHub release notes, and third-party press. The CTA on each card links to the original; the official site is ai.meta.com.
Related text models: GPT, Claude, Gemini, Gemma, Mistral, Grok, Qwen, DeepSeek.