liuzhuang13/DenseNet
Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).
Project directory
Projects
Open-source AI projects tracked by the leaderboard, ordered by GitHub stars.
openmlsys/openmlsys
《Machine Learning Systems: Design and Implementation》 (V2 is launching soon）
xlang-ai/OpenAgents
[COLM 2024] OpenAgents: An Open Platform for Language Agents in the Wild
Rikorose/DeepFilterNet
Noise supression using deep filtering
deepjavalibrary/djl
An Engine-Agnostic Deep Learning Framework in Java
fchollet/ARC-AGI
The Abstraction and Reasoning Corpus
Agenta-AI/agenta
Agenta is a workspace where you and your team build agents and automations.
blei-lab/edward
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
mvanhorn/cli-printing-press
Every API has a secret identity. This finds it, absorbs every feature from every competing tool, then builds the GOAT CLI — designed for AI agents first, with SQLite sync, offline search, and compound insight commands.
cvg/LightGlue
LightGlue: Local Feature Matching at Light Speed (ICCV 2023)
jianchang512/stt
Voice Recognition to Text Tool / 一个离线运行的本地音视频转字幕工具，输出json、srt字幕、纯文字格式
### Overview:
这是一个离线运行的本地语音识别转文字工具，基于 fast-whisper 模型，可将视频/音频中的人类声音识别并转为文字。输出格式包括 JSON、SRT 字幕带时间戳格式和纯文字格式，适用于自行部署后替代 openai 的语音识别接口或百度语音识别等，准确率基本等同于 openai 官方 API 接口。
### Key features:
- 支持多种语言和模型版本，包括 tiny、base、small、medium、large-v3。
- 输出格式多样，支持 JSON、SRT 字幕带时间戳格式和纯文字格式。
- 可以将识别结果导出为多种格式，方便用户选择使用。
- 预编译的 Windows 版本和源码部署版本均可使用。
### Tech stack:
Python
### Why it matters:
该工具提供了一个有效的本地语音识别解决方案，适用于需要语音识别功能但又希望避免网络依赖的场景。它不仅提高了工作效率，还减少了对网络资源的依赖，适用于各种需要离线语音识别的场合。
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**中文简体** | [English](./docs/en/README_EN.md)
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eugeniughelbur/obsidian-second-brain
Persistent memory for Claude Code, Codex and 6 other AI agents, stored as plain markdown in your Obsidian vault. New: Crew, one shared logbook so Claude Code, Codex, Cursor and Grok Bot know what each other did. 48 commands: semantic search, self-rewriting notes, key-less research, scheduled agents.
py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
mlabonne/llm-datasets
Curated list of datasets and tools for post-training.
Spandan-Madan/DeepLearningProject
An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.
idealo/image-super-resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
MegEngine/MegEngine
MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架
rivet-dev/agentos
Tiny, fast, Linux-compatible sandboxes. Powered by WebAssembly.
thunderbird/thunderbolt
AI You Control: Choose your models. Own your data. Eliminate vendor lock-in.
VectifyAI/OpenKB
OpenKB: Open LLM Knowledge Base