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
Kind
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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.
scikit-learn
Simple and efficient tools for machine learning and data analysis in Python.
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
ONNX Runtime
Cross-platform, high-performance ML inference and training accelerator for ONNX models
opencv-python
Pre-built, pip-installable OpenCV bindings that give Python programs full computer vision and image-processing capabilities without compiling from source.
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.
pymilvus
The official Python SDK for Milvus, the open-source vector database for embedding-based similarity search.
onnxruntime-node
Microsoft's official Node.js binding for running ONNX model inference in production JavaScript apps
einops
A readable, framework-independent notation for tensor rearrangement, reduction, and repetition.
Gradio
Build and share machine learning web apps and demos in pure Python.
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
PySpark
Python API for Apache Spark, the unified engine for large-scale distributed data processing
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.
LightGBM
A fast, distributed, high-performance gradient boosting framework based on decision tree algorithms, used for ranking, classification, and other machine learning tasks.
ModelScope
Alibaba's open model-hub library for NLP, CV, speech, and multi-modal AI models.
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.
