Download upload.py from mrunyan1/splaire-haec-sqtl-credible-sets: direct link, hf CLI and curl.
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- Download file 714 Bytes
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https://huggingface.co/datasets/mrunyan1/splaire-haec-sqtl-credible-sets/resolve/main/upload.py
- Command line
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hf download hf://datasets/mrunyan1/splaire-haec-sqtl-credible-sets/upload.py
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curl -L -o upload.py https://huggingface.co/datasets/mrunyan1/splaire-haec-sqtl-credible-sets/resolve/main/upload.py
714 Bytes
| #!/usr/bin/env python | |
| """upload splaire-haec-sqtl-credible-sets to huggingface hub. resumable, parallel.""" | |
| from pathlib import Path | |
| from huggingface_hub import HfApi, upload_large_folder | |
| REPO_ID = "mrunyan1/splaire-haec-sqtl-credible-sets" | |
| STAGING = Path("/scratch/runyan.m/hf_uploads/splaire-haec-sqtl-credible-sets") | |
| api = HfApi() | |
| # expects repo already created on the hub. uncomment to create: | |
| # api.create_repo(repo_id=REPO_ID, repo_type="dataset", exist_ok=True, private=False) | |
| # upload everything in STAGING. handles LFS automatically, resumable across retries | |
| upload_large_folder( | |
| folder_path=str(STAGING), | |
| repo_id=REPO_ID, | |
| repo_type="dataset", | |
| num_workers=4, | |
| print_report=True, | |
| ) | |