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Computer Vision
Useful tools for Computer Vision tasksData Science & Machine Learning
Helpful packages for DS and MLDeep Learning
Useful resources for optimizing Deep LearningMLOps
Packages helpful for ML DevOpsNLP and LLMs
Helpful packages for building and deploying LLMsPrivate tools
Collection of private software usedPython and iPython
General Python packages used for quality of lifeWeb Development and Databases
Tools and packages helpful for building web applications.Stars
🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
Python packaging and dependency management made easy
Toolkit for linearizing PDFs for LLM datasets/training
An extremely fast Python linter and code formatter, written in Rust.
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
Install and Run Python Applications in Isolated Environments
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Code Repository for Machine Learning with PyTorch and Scikit-Learn
这是一个用于显示当前网速、CPU及内存利用率的桌面悬浮窗软件，并支持任务栏显示，支持更换皮肤。
Official inference repo for FLUX.1 models
Fully open reproduction of DeepSeek-R1
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
A high-throughput and memory-efficient inference and serving engine for LLMs
This is the release repository for Fan Control, a highly customizable fan controlling software for Windows.
An extremely fast Python package and project manager, written in Rust.
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A list of cool features of Git and GitHub.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
An open source implementation of CLIP.
Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.
The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices
Make PyTorch models up to 40% faster! Thunder is a source to source compiler for PyTorch. It enables using different hardware executors at once; across one or thousands of GPUs.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite