Machine Learning & Deep Learning Packages
Machine-learning and deep-learning frameworks and model libraries for training, fine-tuning, and serving models (PyTorch, scikit-learn, Transformers).
Packages in Machine Learning & Deep Learning
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PyTorch
A Python-first tensor library with GPU acceleration and a dynamic, define-by-run autograd engine for building and training deep neural networks.
Transformers
State-of-the-art pretrained models for text, vision, audio, and multimodal inference and training.
huggingface_hub
The official Python client and hf CLI for the Hugging Face Hub, for downloading, uploading, and managing models, datasets, and Spaces.
Datasets
One-line loading and fast, Arrow-backed processing for thousands of ML datasets
sentence-transformers
A Python library for computing state-of-the-art sentence, text, and image embeddings, rerankers, and sparse and multi-vector representations.
ONNX Runtime
Cross-platform, high-performance ML inference and training accelerator for ONNX models
accelerate
A thin PyTorch wrapper that runs the same raw training script on CPU, multi-GPU, or TPU with mixed precision, DeepSpeed, and FSDP support.
safetensors
A safe, zero-copy binary format for storing and loading ML tensors without pickle
PEFT
Hugging Face's library of state-of-the-art parameter-efficient fine-tuning methods for large models.
torchaudio
GPU-accelerated audio processing library built on PyTorch, with differentiable transforms, Kaldi-compatible features, and pretrained speech models.
onnxruntime-node
Microsoft's official Node.js binding for running ONNX model inference in production JavaScript apps
Transformers.js
Run Hugging Face Transformers models directly in the browser or Node.js with no server required.
einops
A readable, framework-independent notation for tensor rearrangement, reduction, and repetition.
bitsandbytes
8-bit and 4-bit quantization primitives that make large language models fit and train on far less GPU memory.
diffusers
Hugging Face's modular Python toolbox of pretrained diffusion pipelines, models, and schedulers for image, video, and audio generation.
wandb
Official Python SDK and CLI for the Weights & Biases ML experiment tracking platform
Transformers.js
Run Hugging Face Transformers models directly in the browser with no server or Python runtime required.
timm (PyTorch Image Models)
The largest collection of pretrained PyTorch image models, layers, and training utilities.
PyTorch Lightning
A deep learning framework that organizes PyTorch training code and automates multi-GPU, mixed-precision, and distributed training.
DeepSpeed
Distributed deep learning optimization library for training and serving massive models
PyTorch Lightning
The deep learning framework that separates PyTorch research code from engineering boilerplate, scaling from CPU to multi-node GPU clusters without code changes.
EasyOCR
Ready-to-use Python OCR supporting 80+ languages and all popular writing scripts.
kornia
A differentiable computer vision library for PyTorch, with 500+ GPU-ready ops for image processing, augmentation, and geometry.
NVIDIA NCCL
Optimized primitives for collective multi-GPU and multi-node communication
