←搜索结果

搜索“Hugging Face”

按匹配度 · 共 342 条结果 清除搜索

星期四

  1. Mistral AI精选

    Mistral AI 发布 24B 参数模型 Mistral Small 3

    Mistral AI 发布延迟优化的 24B 参数模型 Mistral Small 3，并以 Apache 2.0 许可开放预训练和指令微调检查点。官方称其 MMLU 准确率超过 81%、推理速度达 150 tokens/s，与 Llama 3.3 70B instruct 表现相当且在同一硬件上快 3x 以上。量化后可在单张 RTX 4090 或配备 32GB RAM 的 Macbook 上本地运行，并已通过 la Plateforme 及合作平台提供。

    Up and to the Left

    ilable on la Plateforme as mistral-small-latest or mistral-small-2501. Explore our docs to learn how to use our models for text generation. We are also excited to collaborate with Hugging Face, Ollama, Kaggle, Together AI, and Fireworks AI to make the model available on their platforms starting today: The road ahead It’s been exciting days for the open-source community! Mistral Small 3 complements large open-source reasoning models like the recent releases of DeepSeek, and can serve as a strong

    匹配字段正文

    #lab#模型发布#部署/工程#开源生态

星期一

  1. Prime Intellect

    Prime Intellect 等发布 7B 宏基因组基础模型 METAGENE-1

    USC、Prime Intellect 与 Nucleic Acid Observatory 合作发布 7B 参数自回归 Transformer 宏基因组基础模型 METAGENE-1，在超过 1.5 万亿碱基对的污水宏基因组 DNA 与 RNA 序列上预训练，用于疫情监测、病原体检测和新兴健康威胁的早期发现。模型采用针对宏基因组序列的 BPE 分词，在病原体检测和宏基因组嵌入基准上取得 SOTA，并演示了病原体与异常检测场景。团队称其 512 token 上下文长度限制了复杂序列设计任务，当前版本风险较低，但未来更大模型开源前需严格安全评估。

    METAGENE-1: Metagenomic Foundation Model

    undation model designed for pandemic monitoring, trained on over 1.5T base pairs of DNA and RNA sequenced from wastewater. Paper: metagene-1-paper; Github: github.com/metagene-ai; Hugging Face: huggingface.co/metagene-ai A collaboration between researchers at USC, Prime Intellect, and the Nucleic Acid Observatory. Overview We pretrain METAGENE-1, a 7-billion-parameter autoregressive transformer language model, which we refer to as a metagenomic foundation model, on a novel corpus of diverse meta

    匹配字段正文

    #company#模型发布#数据/训练#开源生态