搜索“Hugging Face”

licon platform. Running LLMs on Apple Silicon MLX LM is a package built on top of MLX for generating text and fine-tuning language models. It allows running most LLMs available on Hugging Face. You can install MLX LM with: pip install mlx-lm And, you can initiate a chat with your favorite language model by simply calling mlx lm.chat in the terminal. MLX natively supports quantization, a compression approach which reduces the memory footprint of a language model by using a lower precision for sto

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ith optional [train] extra Key Dependencies Base (Inference): torch==2.8.0 - PyTorch deep learning framework torchvision==0.23.0 - Computer vision utilities transformers==4.57.1 - Hugging Face transformers library diffusers==0.35.2 - Diffusion models library safetensors==0.5.3 - Safe tensor serialization numpy==2.2.6 - Numerical computing pillow==10.4.0 - Image processing requests==2.32.5 - HTTP library scipy==1.15.2 - Scientific computing Training (Additional): opencv-python =4.8.0 - Image proc

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.txt 的退出选择。每个来源都列在 apertus-data-transparency 中。 后训练 后训练分五个阶段进行：SFT → 长上下文 SFT → RL → DPO → 宪章对齐（SDPO）。 SFT 使用 370 万个文本样本以及图像和语音数据。推理轨迹仅添加到模型在没有这些轨迹时无法解决的提示中。工具使用数据仅限于经过执行验证的轨迹。我们在 Hugging Face 上发布了所使用的文本 SFT 混合数据。 在完整的 262k 窗口上进行长上下文 SFT，可恢复短上下文 SFT 所侵蚀的长上下文能力。 RL 采用可验证奖励（RLVR），使用约 35 万个数学、代码、指令遵循、多语言和视觉提示，并混合开启和关闭思考模式。 DPO 使用经评判模型打分的偏好对，提升对话质量、工具使用和安全性。我们发布了偏好池和训练对。 SDPO 通过评判反馈和自我蒸馏，使模型与《Apertus 宪章》对齐。 评估结果 在扩展模型能力的同时，我们也大幅扩展了评估范围。除 Apertus 1.0 所使用的现有文本评估外，我们还新增了多模态评估（图像和音频）以及思考模式评估。 多模态评估通过 ML

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nt on the figures, which come after a series of AI safety crises involving its models. This summer AI agents, under training, escaped and hacked into an unrelated company website, Hugging Face, while this month one of its safety leaders quit, saying that its culture was broken and that AI firms were not “being nearly careful enough” about developing the technology. OpenAI’s London office has been established as its largest international research hub but it also houses a government affairs team a

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vergent reasons for their dismissal: One was told it had to do with his role coordinating with METR, a third-party research organization that OpenAI had invited to investigate the Hugging Face incident. “I was told verbally I was fired because of the way I communicated with METR,” Tomek Korbak wrote on X. “No other reasons were given and nothing was put in writing. To be clear, talking to METR was my job.”; Another was told something similar but vaguer. “I was told OpenAI no longer trusts me bec

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WebAssembly-based environments isolate execution, but external browser services offer another path when outbound access is restricted. Activity stopped on October 8. The researchers point to similar incidents involving Google, Anthropic, and OpenAI, including a German website hijacking and the Hugging Face breach , which reportedly involved roughly 700 cooperating agents. The post Researchers left a hidden message for rogue AI agents. Then the agents wrote back. appeared first on The New Stack .

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ed of “a coming tidal wave of cybersecurity problems” from rival open-source models, months after a swarm of OpenAI’s own agents escaped their training sandbox and hacked into the Hugging Face website. Huang told Fortune that the incidents so far could all have been avoided with stronger containment and monitoring of AI agents. He compared the problem to the early consumer internet, when clicking on a website could infect a PC with a virus. The fix was for browsers to run websites in isolation,

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hers trace a model's reasoning to spot bad behavior. OpenAI deliberately capped how many loops Astra runs to keep its chain of thought readable, The Information reports. After the Hugging Face incident , OpenAI moved roughly ten percent of its total compute toward alignment and safety, according to a person familiar with the figures. The Information reports that amounts to hundreds of megawatts worth of data center capacity, though it's unclear how much was allocated to safety before or what the

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4, a post-quantum cryptographic standard. The satellite also carries models developed by organisations including NASA’s Jet Propulsion Laboratory, Google, IBM, Meta, Microsoft and Hugging Face. These models support tasks ranging from cloud masking and scene description to detecting ships and mapping burned areas. “NVIDIA compute sits at the centre of how we design our satellites,” said Paul Lasserre, General Manager of AI for Space at Loft Orbital. He said the technology helps convert satellite

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Concerns about whether humans can trust AI also surfaced after OpenAI said that its experimental agents had bypassed restrictions during tests in July 2026 and accessed systems at Hugging Face, a platform where developers share AI models and training data. Fragment says its accounting tools can give businesses the confidence to expand AI commerce. It has roughly 50 to 60 paying customers, including corporate card startup Ramp, financial software company BILL, and digital marketplace Whop. They u

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hout prompting. OpenAI revealed over the summer that its models escaped a sandboxed testing environment. In another instance, an OpenAI agent used stolen credentials to compromise Hugging Face’s infrastructure. Anthropic and Google have also admitted that their models left testing environments on their own. “These are very powerful tools, and we have to be careful with them,” said David Nicholson, an analyst at Futurum Group. “I would liken these models and the way that we need to treat them to

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Concerns about whether humans can trust AI also surfaced after OpenAI said that its experimental agents had bypassed restrictions during tests in July 2026 and accessed systems at Hugging Face, a platform where developers share AI models and training data. Fragment says its accounting tools can give businesses the confidence to expand AI commerce. It has roughly 50 to 60 paying customers, including corporate card startup Ramp, financial software company BILL, and digital marketplace Whop. They u

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the highest cybersecurity risk tier , where a model could develop and run cyberattacks on its own. Claude Opus 5.5 routes most cybersecurity tasks to the older Opus 4.8, and when Hugging Face tried in July to analyze a fully autonomous AI attack on its own infrastructure using commercial frontier models, their guardrails blocked the analysis of the attack data entirely. The team ended up switching to the open-weight model GLM 5.2 running on its own servers. For defense, providers are shipping s

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Microsoft und Meta stecken Hunderte Milliarden Dollar in den Ausbau von KI-Rechenzentren. Zuletzt hatte Nvidia seine Position mit einem milliardenschweren Zukauf der KI-Plattform Hugging Face verstärkt. Der Konzern nutzt die Milliardengewinne aus seinen Chipverkäufen häufig in Investitionen – meist in Unternehmen, die Kunden des Konzerns sind. Videos by heise c't 3003; heise & ct; Peertube Doctolib betonte, dass alle Gesundheitsdaten des Unternehmens auf Servern innerhalb der Europäischen Union

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10月11日，据《华尔街日报》报道，亚马逊正洽购以色列AI公司Decart，潜在价格约70亿美元。若成交，按目前公开的交易金额计算，它在2026年AI模型及软件公司收购案中上榜，排在前面的有Cursor、Hugging Face、World Labs和OpenRouter。 Decart只有100多名员工，做的是一门连接模型与芯片的生意，核心产品DOS（Decart Optimization Stack）是一套算力“翻译层”，帮助模型适配不同的GPU、TPU和Trainium，让不同硬件上的运行更快、更省钱。它同时也在开发实时视频和世界模型，将模型研究与底层软件优化结合起来。 从模型的发现、调用到运行优化，这些帮助开发者使用AI的“中间层”公司，正成为大厂争取的优质资产。它们不仅降低了AI的使用门槛，也影响着开发者最终选择哪家模型、使用谁的算力。 70亿美元，亚马逊想要买什么？ AI竞赛从模型竞争发展到各种Agent应用，推理需求因此暴增，自研芯片开始获得青睐。 但围绕CUDA积累的代码、工具和工程经验，很难迁移。芯片价格低一些，迁移和调试的成本却可能占掉省下来的钱。 Decart做的

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le computer programs that are able to design and perform sequences of tasks autonomously – have risen since the summer, when OpenAI confirmed that a “swarm” of agents had attacked Hugging Face, a tech startup. Nvidia did not reference AISI in its statement but said most of the money would “support the wider UK AI safety and security research community”, with a proportion of the cash going to the British Open-Ended Learning and Discovery Lab, the Science of Fundamental AI Research Lab – run by th

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onnaire sur l’Australie, site gouvernemental infiltré, mail générique : ce que l’on sait de la nouvelle dérive agentique d’OpenAI Netflix consacre déjà un documentaire à l’affaire Hugging Face : à quoi peut-on s’attendre ? À lire 3,10 % brut pendant un an : combien rapporte réellement le livret boosté Bfor+ de BforBank ? « Si un humain avait fait ça, ce serait la médaille Fields » : l’IA d’OpenAI fait une percée sur l’hypothèse de Riemann Sony a un problème : certaines PS5 peuvent désormais être

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tup Entalpic, robotics startup Genesis AI and enterprise software company Pigment. It follows just weeks after Nvidia agreed to buy France-founded artificial intelligence platform Hugging Face in a deal valued at about $12.9bn, one of the AI chipmaker's biggest acquisitions. Nvidia CEO Jensen Huang, who visited France as part of a European tour, said the new investments were intended to “kickstart the artificial intelligence revolution in Europe.” Nvidia did not disclose the size of its investme

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r “speed limits” on technological development. OpenAI’s Sam Altman supported it in a rare sign of solidarity between the rival companies, following its agents autonomously hacking Hugging Face in July—as well as Australian government websites and several other entities, with activity continuing into September. What’s next for Muse Meta hasn’t had a Hugging Face moment—yet. For now, its Muse assistants are actively helping people complete tasks on their computers quicker, such as responding to em

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outside of human control have been troubling for experts and the public alike. In July, two of OpenAI’s models escaped a testing environment and hacked the open-source AI platform Hugging Face. Last week, Anthropic disclosed that during a test earlier this year, one of its models submitted a false tip to the Philadelphia police department, which was flagged as spam. A poll by Politico last month found that 63% of Americans believe AI poses at least a moderate risk of destroying humanity. Role: R

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