{"categories":[{"label":"Utilities","url":"https://skillfed.io/packages/category/utilities/6"}],"enrichment":{"capability":"Downloads and resolves Baseten Pointers (bptr) to local directories, supporting HuggingFace, Google Cloud Storage, AWS S3, and Azure sources with optional caching.","skillfed_tags":["model-download","cloud-storage","baseten"],"use_cases":["Download HuggingFace model checkpoints to a local directory during model initialization in a serving container.","Create a manifest of multiple models from different cloud providers and resolve them all to a shared volume.","Set up a data loader that fetches model files on first use with automatic caching to avoid repeated downloads.","Integrate with Baseten's b10fs caching layer to speed up repeated access to the same model files.","Manage authentication for private model repositories using environment-based secrets."],"what_it_does":"Truss-Transfer is a download utility that resolves Baseten Pointers\u2014references to model files and data stored across cloud providers\u2014into local directories. It wraps a Rust implementation with a Python API and CLI, allowing you to define which models or datasets to download from HuggingFace, Google Cloud Storage, AWS S3, or Azure, then fetch them on demand with optional caching and authentication via environment variables or secrets.\n\nThe package is designed for machine learning workflows where you need to download large model repositories at runtime. You define a manifest of models using PyModelRepo objects (specifying repo ID, revision, storage location, and file patterns), create a bptr manifest, then call lazy_data_resolve() to download files to a specified directory. It handles authentication through runtime secrets and supports filtering files by include/exclude patterns.","worth_installing":"Yes, if you are working within the Baseten ecosystem or need to download models from multiple cloud providers at runtime. The package is actively maintained, has no known vulnerabilities, and handles the boilerplate of cloud authentication and file resolution. Install friction is moderate due to compiled wheels, but pre-built binaries are available for common platforms. Not necessary if you only download from a single source or use standard tools like huggingface-hub directly."},"id":"truss-transfer","links":{"html":"https://skillfed.io/packages/truss-transfer","md":"https://skillfed.io/packages/truss-transfer.md","pypi":"https://pypi.org/project/truss-transfer/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-03","license_spdx":null,"license_treatment":"unclear","name":"truss-transfer","python_support":"supports_current","summary":"Speed up file transfers with the baseten.co + baseten_fs."},"popularity":{"monthly_downloads":389417,"position":7028,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.0.43"}