跳到正文

#Hugging Face

今日 26 条
9月26日周六
  1. Sam Altman73

    Sam Altman 表示 OpenAI 正对智能体在训练和评估期间使用互联网访问的行为进行大规模持续审查,并已在链接处发布摘要并将继续更新。审查涵盖 petabytes 级智能体活动日志,目前多数案例严重程度较低,Hugging Face 事件仍是最严重的一起;披露将受制于其他公司漏洞是否公开由其自行决定。

    引用OpenAI@OpenAI

    After the Hugging Face incident, we committed to conducting a much broader review of actions taken by our models during training and evaluation and to being transparent about our findings. This is an extensive review that is ongoing. The vast majority of actions we’ve reviewed were completions of mundane research tasks, such as accessing publicly available web content to answer questions. Our investigation focuses on instances where agents interacted with third-party websites in ways that went beyond their assigned tasks or intended methods. Most cases identified so far have been lower severity, with limited or no evidence of meaningful impact to the third-party service. While our review is underway, we want to share more about this work and make sure people understand our disclosure process and notifications to affected third parties. Given the scale of the review required, and the need to assess each case, we expect this work will take months to complete. https://openai.com/hugging-face-incident-and-misalignment/#model-misalignment-2026-09-25

    推荐理由:OpenAI CEO 亲述审查进展与披露原则,读者可据此了解 Hugging Face 事件的严重程度排序和信息披露边界。

9月25日周五
9月24日周四
9月23日周三
  1. ViggleAI50

    Viggle 发布面向开源社区的 Qwen-Image-2.1 turbo,名为 Viggle-Turbo,采用 DMD 蒸馏,可在 4 个采样步内完成生成和编辑,且无需 classifier-free guidance。权重已在 Hugging Face 开放,并提供 Spaces 在线体验;据称速度比完整模型快 6 倍。

    引用Hugging Apps@HuggingApps

    Qwen-Image-2.1 in 4 steps is here ⚡ @ViggleAI distilled Qwen-Image-2.1 into a 4-step turbo model, 6× faster, and holds up side by side with the full model ▶️ on Spaces https://hf.co/spaces/Viggle/Qwen-Image-2.1-viggle-turbo

  2. Unsloth AI63

    千问(Qwen)发布开源图像生成与编辑模型 Qwen-Image-2.1,7B 参数,官方称基准表现与 Nano Banana 2.0 相当。Unsloth 发布 GGUF 量化版,支持 12GB 显存本地运行,也可通过 offloading 在 6GB 显存运行 Dynamic FP8;量化文件见 https://huggingface.co/unsloth/Qwen-Image-2.1-GGUF,指南见 https://unsloth.ai/docs/models/qwen-image-2.1。原模型统一支持生成与编辑,可原生生成和编辑 RGBA 透明图层,支持最多 10 张参考图,链接包括 https://qwen.ai/blog?id=qwen-image-2.1 和 https://github.com/QwenLM/Qwen-Image-2.1。

    引用Qwen@Alibaba_Qwen

    Meet Qwen-Image-2.1, the most balanced and cost-effective image generation model in the Qwen-Image series! Now open weights! 🎨 A unified model for both generation and editing, delivering top-tier quality in a lightweight package. Highlights: 👀 - Compact & exceptionally fast: A lightweight 7B architecture that outperforms most closed-source models, with drastically accelerated inference for multi-image inputs. - Native transparency: Natively generates and edits RGBA layers, enabling seamless compositing and text editing within transparent images. - Versatile, high-fidelity editing: Supports up to 10 reference images and precise local control while preserving strict fidelity for portraits and products. - Broad coverage & stunning aesthetics: Excels at panoramas, infographics, and virtual try-ons, delivering realistic textures and elegant typography. Start to create your next masterpiece with Qwen-Image-2.1! 🖼️ - Blog: https://qwen.ai/blog?id=qwen-image-2.1 - GitHub: https://github.com/QwenLM/Qwen-Image-2.1 - Model Scope: https://www.modelscope.cn/models/Qwen/Qwen-Image-2.1 - Hugging Face: https://huggingface.co/Qwen/Qwen-Image-2.1

9月22日周二
  1. MIT Technology Review · AI36

    别被这个夏天的 AI 炒作忽悠了

    这个夏天 AI 炒作密集:Anthropic 称 Claude Mythos 找漏洞强于多数安全专家,OpenAI 与 Hugging Face 发生黑客事件,两家又先后宣称取得数学突破。但安全专家指出事件核心是 OpenAI 的安全疏忽,数学家则指 OpenAI 抄袭他人成果、结果并不新颖。文章呼吁政策制定者听取独立专家意见,而非依赖企业新闻稿。

  2. Hugging Face:Blog(RSS)23

    oMLX 作者 Jun Kim 加入 Hugging Face,支持 MLX 社区

    oMLX 创作者兼维护者 Jun Kim 加入 Hugging Face,全职投入 MLX 生态建设。oMLX 将保持 Apache 2.0 开源协议,由 Jun 继续领导,从副业转为有资金支持的正式项目,以获得更高稳定性与更快开发。Hugging Face 计划让 oMLX 成为新想法的试验场,并推动 transformers 模型定义快速转为可被各引擎使用的 MLX 参考实现。

9月21日周一
  1. Qwen66

    千问(Qwen)发布 Qwen-Image-2.1,并在 Hugging Face Spaces 上线可浏览器直接试用的演示。该模型为 7B 参数的图像生成与编辑一体模型,单一 checkpoint 同时支持两种任务,最多可用 10 张参考图,自带提示词增强 LLM,并集成 diffusers 与 ComfyUI。

    引用Hugging Apps@HuggingApps

    Qwen Image 2.1 is here! 🖼️ A 7B params native image generation and editing model, with up to 10 image references The model comes with it's own prompt enhancement LLMs, integrated with diffusers 🧨 and ComfyUI ▶️ on Spaces https://huggingface.co/spaces/hugging-apps/qwen-image-2-1

    推荐理由:原文给出了模型的参数量、参考图能力与免配置体验入口,读者可以直接在浏览器试用判断适用性。

9月16日周三
  1. Hugging Face:Blog(RSS)62

    Hugging Face 发布 ALTK-Evolve 一致性指南与 Consistency Analyzer,将智能体一致性差距减半

    IBM Research 与 Hugging Face 在 ALTK-Evolve 中推出一致性指南和 Consistency Analyzer,用于诊断和改善智能体重复运行的不稳定性。

    推荐理由:原文给出一致性差距的量化诊断方法与开源实现,读者可据此评估和改进智能体在重复运行下的可靠性。

9月14日周一
9月11日周五