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2 repositorios

Awesome GitHub RepositoriesContact-Gated Access

Requires users to share contact information before accessing a repository's files.

Distinct from Secure File Access: Distinct from Secure File Access: focuses on gating access behind contact information sharing, not general secure file exposure.

Explore 2 awesome GitHub repositories matching security & cryptography · Contact-Gated Access. Refine with filters or upvote what's useful.

Awesome Contact-Gated Access GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • huggingface/huggingface_hubAvatar de huggingface

    huggingface/huggingface_hub

    3,342Ver en GitHub↗

    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

    Requires users to share contact information before accessing repository files.

    Pythondeep-learninghacktoberfestmachine-learning
    Ver en GitHub↗3,342
  • huggingface/hub-docsAvatar de huggingface

    huggingface/hub-docs

    506Ver en GitHub↗

    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

    Requires users to accept terms or provide information before granting access to sensitive datasets.

    Handlebarshacktoberfestmachine-learning
    Ver en GitHub↗506
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