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Stable-audio-tools is a toolkit for training and deploying latent diffusion models for high-fidelity audio synthesis. It provides a framework for generating audio by iteratively refining noise within a compressed latent space, using specialized encoders to preserve temporal and spectral features of the audio signal. The project features a system for adapting pre-trained audio checkpoints to new datasets through modular initialization and configuration files. It includes utilities for weight extraction and inference model export, which remove training metadata and optimizer states to create li

The Hugging Face Hub Python client is a library that provides programmatic access to the Hugging Face Hub, a centralized platform for hosting and collaborating on machine learning models, datasets, and demo applications. It serves as the primary SDK for interacting with the Hub's API, enabling users to download and upload models and datasets, manage repositories, authenticate via tokens or OAuth, and run inference on hosted models through a unified interface. The client distinguishes itself through a comprehensive set of capabilities that go beyond basic file transfer. It includes a CLI exten

This repository serves as the documentation source for the Hugging Face Hub, a collaborative platform designed for hosting, versioning, and discovering machine learning models, datasets, and interactive applications. It provides the foundational infrastructure for managing machine learning assets through Git-based repositories, which support large file storage, branching, and comprehensive commit history. The platform distinguishes itself by integrating metadata-driven discovery and structured management systems that allow users to attach licensing, task categories, and performance metrics to