开发者工具1 month ago
ModelBrew — AI you don't have to double-check
用您的数据微调语言模型并管理自定义事实，获得密码学删除证明。
@MBrew26730 · X
Dataset cleaning + fine tuning + continual learning at
完整作品展
技术栈
60 projects
用您的数据微调语言模型并管理自定义事实，获得密码学删除证明。
@MBrew26730 · X
Dataset cleaning + fine tuning + continual learning at
LLM驱动的新闻聚合器，实时呈现和更新热门故事。
tdubey · HN
DWS A LLM Generated, "Drudge Report" style news site
查找与您硬件兼容的AI模型并查看性能和价格估计。
cdnsteve · HN
Tokenstead, find AI models for your hardware
Format-agnostic LLM hub. Bring your own provider keys and route across Anthropic, OpenAI, ChatGPT/Codex, Kimi, Alibaba DashScope, and AWS Bedrock — with unified observability and c
@0xxmemo · X
检测LLM API是否被降智或偷换模型，一键跑6项探针得出结果
cocodot LLM 降智检测 — 免费的 LLM API「降智/偷换模型」在线检测：填入任意 OpenAI 兼容端点的 base_url 和临时 API Key，跑 6 项探针（模型声明、动态题、能力完整性等）生成分项报告；Key 仅用于当次检测、不落库不留存，检测方法[开源](https://github.com/cocodot2026/cocodot-llmprobe)
估算llama.cpp模型推理所需的显存大小
hypfer · HN
According to this shitty vibecoded thing "I" built https://hypfer.github.io/will-it-fit-llama-cpp/ (and I guess according to math too), FP16 K/V would give me something like 90k context at the same model quant, which doesn't really fit my usage. But maybe someone else has experience to share there
开源LLM和视频模型的OpenAI兼容API
bingus-bongo · HN
Use GLM-5.3 in Cursor today via tokengo API
实时可视化硬件在运行LLM推理时的性能指标
dev_dan_2 · HN
WatchMachineGo – A visualizer to show hardware performing LLM inference
通过隐私保护的API访问中国开发的开源AI模型。
@Jenny5143197635 · X
查看 GPU 兼容的 LLM 模型及成本预算方案。
jaeseok614 · HN
Open-source calculator for "will my GPU run this LLM?"
在浏览器中测试小型语言模型（8M-13M 参数），离线可用。
u/Live_Confusion_3003 · Reddit
I trained an LLM that runs on an ESP32 and directly in the browser Link to try it out yourself is: topk.sh The models download their weights directly in the browser so it works offline. Keep in mind they are very small and inaccurate. (8M and 13M parameters) However, I am building 500M and 1B+ parameter local models for agent based coding and other purposes. I will be shipping hardware designed for these tasks which connect directly to you computer or other device.
