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An opinionated list of awesome Python frameworks, libraries, software and resources.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
A high-throughput and memory-efficient inference and serving engine for LLMs
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
PyTorch Tutorial for Deep Learning Researchers
The fundamental package for scientific computing with Python.
Fast and memory-efficient exact attention
SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
Modular visual interface for GDB in Python
Large Language Model Text Generation Inference
Hydra is a framework for elegantly configuring complex applications
GEF (GDB Enhanced Features) - a modern experience for GDB with advanced debugging capabilities for exploit devs & reverse engineers on Linux
A flexible package manager that supports multiple versions, configurations, platforms, and compilers.
Simple examples to introduce PyTorch
Snips Python library to extract meaning from text
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Built by researchers, for research.
PyTorch native quantization and sparsity for training and inference
A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".
Embedded Rust device crates for STM32 microcontrollers
Aggegration of ARM Cortex-M (and other) CMSIS SVDs and related tools
Modular hardware build system
Infrastructure for Machine Learning Guided Optimization (MLGO) in LLVM.
Hierarchical unsupervised and semi-supervised topic models for sparse count data with CorEx
Powering AWS purpose-built machine learning chips. Blazing fast and cost effective, natively integrated into PyTorch and TensorFlow and integrated with your favorite AWS services