UPLOAD.md

Upload this dataset to Hugging Face

The dataset card is README.md. The three JSONL configurations load without a custom dataset-loading script.

The destination is chembricks/chemistry-knowledge, the existing ChemBricks dataset repository. Authenticate by supplying an HF_TOKEN environment variable with write access to that destination. Keep credentials out of this folder and out of chat.

Run these commands from this dataset directory. The card already names the destination; after any local edits, regenerate it, then seal and verify the package:

python -B write_card.py --repo-id chembricks/chemistry-knowledge
python -B verify.py --seal
python -B verify.py

The optional uploader requires jsonschema and the official huggingface_hub package. Install them in your chosen Python environment if needed: python -m pip install jsonschema huggingface_hub. It validates the package, creates the named dataset repository if needed, and uploads only the files named in the manifest. Local build files, caches and credentials are not included.

python -B upload.py --repo-id chembricks/chemistry-knowledge

To create a private repository for an initial inspection, add --private. This flag controls creation of a new repository; it does not change the visibility of an existing one.

After upload, check that the records, claims and evidence configurations are visible in the dataset viewer and that the figure renders. Record the resulting dataset URL and immutable Hub revision in your release announcement. A DOI is optional and can be added later; none is claimed by this package.

A DOI, paper, gated-access agreement and custom loader are not required. The package already supplies the dataset card, MIT license, citation metadata, schemas, provenance, checksums, curation policy, examples and upload tooling. It deliberately supplies no train/test split: see CURATION.md before constructing an evaluation.

References: Hugging Face dataset cards, data configurations, and uploading folders.