UPLOAD_GUIDE.md

Upload this release to Hugging Face

Suggested repository slug: AILITH-Beyond-Reinforcement-Learning
Repository type: Dataset, used here to host research artifacts.
Display name: AÍLITH — Beyond Reinforcement Learning

The kit is prepared for upload. No Hugging Face repository has been created or changed by its preparation.

Windows uploader

1. Extract the complete release ZIP to a normal folder.
2. Open AILITH_HuggingFace_v0.5.0 and double-click UPLOAD_TO_HF.bat.
3. Follow the standard Hugging Face login if needed. Enter the repository name or paste its dataset URL.
4. Choose visibility for a new repository, review the displayed destination, and start the upload.

The launcher prepares an isolated Python environment and installs the Hub client when needed. Python 3.10 or newer and internet access are required. If Python is missing, the launcher explains how to install it.

The uploader checks SHA256SUMS before upload and selects only the listed release files plus that checksum file. Repository contents are uploaded at the root so the card and relative links work. Other remote files are kept, and an existing repository retains its visibility. Transient failures can be retried; an interrupted upload can be rerun to the same destination.

See UPLOADER_README.md for offline preview, command-line options, and recovery instructions. The uploader-only download also works with the earlier release folder or its outer ZIP.

Browser upload

1. Create a dataset repository under your chosen account or organization. Choose its visibility in the creation form.
2. Extract the outer AILITH_HuggingFace_Release_v0.5.0.zip.
3. Open its AILITH_HuggingFace_v0.5.0 directory.
4. Upload the contents of that directory into the repository root. README.md must be at the root, alongside LICENSE, citation files, and the artifact directories.
5. Commit, then check that the card renders and that its PDF and full-archive links work.

Uploading only the outer ZIP will leave the root card and its links unavailable to Hub rendering. The original research ZIP under releases/ should remain a ZIP; it is the downloadable reproducibility package.

CLI upload

The current Hugging Face CLI is hf. Install the Hub package and authenticate using its standard interactive login:

python -m pip install --upgrade huggingface_hub
hf auth login

From the directory containing AILITH_HuggingFace_v0.5.0, replace YOUR_NAMESPACE with your actual account or organization:

hf repos create YOUR_NAMESPACE/AILITH-Beyond-Reinforcement-Learning --repo-type dataset
hf upload YOUR_NAMESPACE/AILITH-Beyond-Reinforcement-Learning ./AILITH_HuggingFace_v0.5.0 . --repo-type dataset --commit-message "AÍLITH v0.5.0: complete research release"

Add --private to repository creation if that is the visibility you want. For an existing repository, skip creation and upload to the selected repository ID. The commands do not request file deletion or alter visibility of an existing repository. Obtain exact local option details with hf repos create --help and hf upload --help if your installed CLI differs.

Description

Copy REPOSITORY_DESCRIPTION.txt into a short-description field where available. The detailed publication text is already in README.md; its YAML declares English, the existing MIT license, and relevant research tags. The manuscript title and requested author remain unchanged.

Metadata and citation

This is an artifact release rather than a pretrained model or conventional row-based training dataset. A dataset preview is not required for reading the manuscript or running the software. No model task tag, trained weights, DOI, or arXiv identifier is supplied. Add an actual repository URL or DOI to the citation files only after one exists.

The official references used for this upload layout are the dataset-card documentation and Hub upload guide, checked on 18 October 2026.