USASI
SoftwareFramework

Transformers

Version 5.17.0

Maintained by Hugging Face13

Transformers is Hugging Face's open-source Python library of model definitions for text, vision, audio, video, and multimodal models, used for both inference and training. Its README presents it as a shared model-definition layer that other training frameworks and inference engines build on, and it loads pretrained checkpoints from the Hugging Face Hub.12

Last reviewedEntry updated Documented release Unknown

Availability and license

Overall availability

Public

Source code on GitHub under the Apache License 2.0; installable with pip or uv, or from conda-forge.134

Availability is separate from permission: read the license before using or redistributing.

Public materials checklist

Items for a framework under USASI rubric v0.1. Unknown means unassessed or insufficient evidence.
Public materials checklist for Transformers
ItemStatusNotes and evidence
Source codeIs the source code publicly readable?Public1
DocumentationIs user documentation published?PublicInstallation, quickstart, and API documentation are published on the Hugging Face docs site.42
InstallationAre installation instructions or packages publicly available?PublicDocumented installation with pip or uv (for example the transformers[torch] extra), from source, as an editable install, and from conda-forge.4
Supported platformsAre supported operating systems or hardware documented?PublicThe installation guide states the library works with PyTorch and is tested on Python 3.10+ and PyTorch 2.5+, and documents setups for NVIDIA GPUs (CUDA), Intel GPUs (XPU), CPU-only use, and NVIDIA ARM64 devices.4
Release statusAre versioned releases published?PublicVersioned releases are published on GitHub; v5.17.0 was published on 2026-09-09.5

What it is useful for

Loading and running pretrained models through the high-level Pipeline API or model classes, fine-tuning them, and serving or chatting with a model from the command line.2

Run and use notes

Documented facts only. No hardware or performance claims are made without a cited source and stated assumptions.
  • The installation guide documents offline use: download a model repository in advance and set HF_HUB_OFFLINE=1 (or pass local_files_only=True) so that loading does not contact the Hub.4

Organization context

U.S. eligibility

Project eligibility rests on documented governing or maintaining entities, not on contributors.

Eligible · basis: U.S.-governed project

Transformers is developed in Hugging Face's GitHub organization and its LICENSE names the Hugging Face team as copyright holder. Hugging Face's terms of service identify Hugging Face, Inc., a Delaware corporation, as the provider of its services, under New York law and courts, and its privacy policy states that the company and its servers are located in the United States (the French entity is named as its EU main establishment). See the hugging-face organization record for the full dual-country assessment.1367

Assessed Sep 29, 2026

Sources

  1. 1.
    huggingface/transformers (external site: github.com)

    Hugging Face · Repository · accessed Sep 29, 2026

  2. 2.
    Transformers README (external site: raw.githubusercontent.com)

    Hugging Face · Documentation · accessed Sep 29, 2026

  3. 3.
    Transformers LICENSE (external site: raw.githubusercontent.com)

    Hugging Face · License · accessed Sep 29, 2026

  4. 4.
    Installation (Transformers documentation) (external site: huggingface.co)

    Hugging Face · Documentation · accessed Sep 29, 2026

  5. 5.
    Release v5.17.0 · huggingface/transformers (external site: github.com)

    Hugging Face · Release notes · published Sep 9, 2026 · accessed Sep 29, 2026

  6. 6.
    Terms of Service (external site: huggingface.co)

    Hugging Face · Official page · accessed Sep 29, 2026

  7. 7.
    Hugging Face Privacy Policy (external site: huggingface.co)

    Hugging Face · Official page · accessed Sep 29, 2026

This listing is not an endorsement, a safety assessment, or a federal approval.

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