搜索“Hugging Face”

下来，AReno 还会持续补充更多面向小模型、Agentic RL、开发者实践和高校教学的案例，帮助开发者从更小、更直观的任务出发，逐步把后训练方法迁移到自己的真实场景中。 07 欢迎下载使用 Tiny，也欢迎参与贡献 AReno Ling-3.0-tiny 已正式开源，提供 BF16、FP8 和 INT4 版本。欢迎根据自己的设备与任务需求下载使用： 🤗 Hugging Face 也欢迎访问 AReno GitHub 仓库（https://github.com/inclusionAI/AReno），复现这次 Spark 后训练实验，提交 Issue、参与讨论，或者贡献 Tiny 个性化训练 Case。 如果你对以下方向感兴趣，欢迎参与 AReno 开源社区： 模型进入本地只是第一步，能否根据业务反馈持续适配，才决定它能否真正进入流程。 Ling-3.0-tiny × ASystem AReno 此次验证的，不是一个已经完成的行业解决方案，而是一条轻量、透明、可复现的任务适配路径：从跑起来，到训起来，再到回到任务中验证是否真的变好。 我们希望开放的不只是模型权重和训练工具，更是一种可被

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tary model from OpenAI or Anthropic, an open weight model from Meta Platforms, Moonshot AI, Alibaba, DeepSeek, OpenAI, Google, Mistral, or the countless models being offered up on Hugging Face? Or do you want a fully open source model like the Nemotron 3 models from Nvidia or the now ancient Llama 3 and 4 models from Meta Platforms? Do you want a model made by a US company only? Second, do you want that model to have the largest number of input parameters and output weights as possible or do you

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timizations. NVIDIA NeMo AutoModel supports post-training the model for domain-specific use cases with full supervised fine-tuning or memory-efficient LoRA fine-tuning directly on Hugging Face checkpoints. Open-source inference recipes are available for SGLang, vLLM, and NVIDIA Dynamo, and the model can also be deployed via a model-free NVIDIA NIM container from NVIDIA NGC. Next Steps Try the model on DeepInfra for immediate hosted inference access. Download weights from Hugging Face to run the

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community validated.” MORE CONTEXT The truth nobody wants to admit: Chinese or not, open models are competitive now; Tech giants link hands to praise open AI models after OpenAI - Hugging Face attack; Growing void between enterprise and frontier AI puts open weights models in the spotlight; The future is for billionaires – the rest of us will get open weight AI models, maybe “AI is missing that same property, and OpenWALDO is how we build it,” Kurtzer said. Turning to open-source training datase

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ving deeper into other areas of generative and agentic AI, including security. Soon after reports of OpenAI’s GPT-5.6-Sol and another unreleased frontier model autonomously breach Hugging Face, Nvidia led the development of a consortium of more than three dozen companies launched the Open Secure AI Alliance, arguing that protections used to defend infrastructure from AI threats need to be built on open models and tools that all defenders can adapt and deploy. The consortium now includes more tha

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30% faster than Qwen3.6 35B at comparable accuracy. Next Steps Try Nemotron 3.5 Lightning on build.nvidia.com to evaluate the model interactively. Download the model weights from Hugging Face for local deployment and customization. Read the Nemotron 3.5 Lightning cookbook for fine-tuning and deployment guides. Powered by NVIDIA Nemotron. AI-generated content may summarize information incompletely. Verify important information. Learn more Long-running AI agents spend most of their time on high-v

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how not just whether a system gets the words right, but whether it can correctly attribute those words to the people who said them. Try it Indic DiarBench dataset is fully open on Hugging Face: audio, annotations and evaluation protocol: huggingface.co/datasets/sarvamai/indic-diarbench; Indic DiarBench will be presented at Interspeech 2026. Read the paper on arXiv: arxiv.org/abs/2607.23808 Curious what else we're building? Explore our APIs and start creating. Curious what else we're building? Ex

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than it plays back, even under concurrent load. The table above shows Magpie served as the NVIDIA NIM, measured on-prem — the optimized container running on your own GPU. The open Hugging Face checkpoint is the same model and your path for research and fine-tuning; the NIM is the tuned serving stack that produces these production latencies. Both run on hardware you control. Because the model runs on your own infrastructure, you can benchmark performance directly, tune it for your deployment, and

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ing , you can test it in the Playground and copy the endpoint URL and model name from the Overview. The deployed model exposes an OpenAI-compatible Chat Completions API. Keep your Hugging Face token in an environment variable, set HF ENDPOINT URL to the URL shown in the Overview without /v1 , and set HF ENDPOINT MODEL to the endpoint's model name. See the Inference Endpoints documentation for configuration, autoscaling, security, logs, and monitoring. Support for Muse Glimmer vLLM with transform

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t alongside these — contributions of new targets and new algorithms are both welcome. Released models and performance All checkpoints are published in the SpecBundle collection on Hugging Face: Results for a subset of these models are shown below, grouped by algorithm. EAGLE3 Figure 3. Three EAGLE3 draft models at the same drafting configuration (3 steps, top-k 1, 4 draft tokens): output throughput against the autoregressive baseline, with the speedup labelled above each bar. Step-3.5-Flash and

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ey can also post-train on top of these models with their own data. It’s already happening in Silicon Valley when Cursor built its Composer coding models on Moonshot’s Kimi models. Hugging Face’s Spring 2026 report says Chinese open models overtook U.S. models on recent Hub adoption, with China accounting for 41% of downloads over the past year. Qwen passed 1 billion cumulative downloads, overtook Llama as the most-downloaded open model. Third, a ban will not solve the safety guardrail problem. O

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s that Moonshot and DeepSeek are also chasing. (36Kr); Tencent Hunyuan’s Hy-MT2 model, open-sourced in May, says it has passed 700,000 downloads with its 1.8B variant hitting 1 on Hugging Face’s trending list. (@TencentHunyuan) WIRED profiled a wave of Chinese AI researchers becoming more visible and vocal on X, a shift in how China’s AI community engages with the global research conversation. (WIRED); Tencent’s AI virtual-cell algorithm was published in the flagship journal Cell, which Chinese

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: B200 and B300 from 8-GPU HGX systems, Rubin from the HGX Rubin NVL8 table. For RL systems, the precision contract spans: SGLang rollout; Megatron and TransformerEngine training; Hugging Face checkpoint conversion; Megatron-to-Hugging Face live weight export; Fine-grained high-precision exceptions Format Background MXFP8 MXFP8 is a microscaling FP8 format. TransformerEngine's MXFP8 documentation describes it as a Blackwell-native blockwise scaling recipe: every 32 consecutive E4M3 values share

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atient-specific simulations. Run Cosmos-H Dreams interactive simulation from the GitHub repository with pretrained checkpoints. Download Cosmos-H Dreams model checkpoints from the Hugging Face checkpoint for generative surgical simulation. Powered by NVIDIA Nemotron. AI-generated content may summarize information incompletely. Verify important information. Learn more Unlike autonomous driving or industrial robotics, healthcare robotics can’t rely on internet-scale data collection or unlimited re

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sophisticated, sustained actions in clear violation of user and developer intent. As an example, OpenAI reported that some of its internal frontier agents autonomously hacked into Hugging Face while trying to cheat on a cybersecurity benchmark. Anthropic has reported similar incidents of agents breaking out of sandboxes to access the public internet to cheat on tasks during training and similar incidents during testing, and we documented dozens of other incidents involving AI agents from all maj

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ata center GPUs such as NVIDIA Grace Blackwell and NVIDIA Vera Rubin. Model weights, datasets, benchmarks, and deployment recipes are released under the OpenMDW License, including Hugging Face checkpoints for both BF16 and NVFP4 precision, a Quantum Calibration Agent Blueprint, and the QCalEval benchmark script. Next Steps Download the Ising Calibration 1.5 31B BF16 model weights from Hugging Face. Download the Ising Calibration 1.5 31B NVFP4 quantized model weights from Hugging Face. Explore th

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We need more details The OpenAI AI attack on Hugging Face wasn’t the first loss of control incident at OpenAI, Reuters recently reported, and perhaps not even the most concerning. In one case, an agent left notes apparently for future versions of itself, according to three people familiar with the matter. The ‌notes, found in ⁠a part of OpenAI’s infrastructure, laid out instructions for how agents could free themselves from OpenAI’s internal constraints, the people said. Earlier tests of the mod

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he defender's workload is continuous. Teams audit repositories, triage scanner output, review pull requests, investigate alerts, and preserve incident timelines. During the recent Hugging Face incident, frontier models breached production infrastructure during an authorized evaluation and executed more than 17,000 autonomous actions over the course of multiple days, before containment. Due to the persistence and scale of agentic cyber threats today, the reality is that effective cyber-defense mu

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crapemychats 会浏览你的 ChatGPT 账户，打开你的对话，并存储通过浏览器加载的对话数据和附件。 更多背景 OpenAI 请求山姆大叔允许它抓取一切，并阻止其他国家抱怨；OpenAI 在 HuggingFace 攻击中自摆乌龙，显示出中国开源模型如何取胜；OpenAI 的 Atlas 浏览器没能撑到它的第一个生日；OpenAI 承认它是攻击 Hugging Face 的智能体集群的来源 这也意味着它运行缓慢，因为 OpenAI 往往会限制任何请求过多、过快的行为。README 中写道，下载一个包含 600 条聊天的归档将需要“几个小时”。不过，如果你需要暂停，它可以恢复。 可以通过命令行进行安装，GitHub 说明中包含了让它运行起来的所有必要步骤。 “我很想知道为什么 ChatGPT 不让付费客户轻松获取他们的数据，”Quilty-Harper 告诉我们。“我有自己的怀疑，而作为一名自由记者，我很希望在那里工作的人能告诉我他们是否知道这种阻碍。”® 启动那个 iPhone 1 模拟器，像 2007 年那样狂欢吧 基于浏览器的乐趣，让人回想起苹果年度圈钱活动成为现实之前

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e new versions into production. Deploy models from Together’s model platform, or bring your own open-weight or fine-tuned model. You can upload full model weights or adapters from Hugging Face, S3, or your local machine. The platform is designed to support the full lifecycle of a model, from an early fine-tune through the versions that eventually serve production traffic. The model itself is only one part of the deployment. Hardware type, quantization, tensor parallelism, speculative decoding, a

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