القائمة
Use when setting up Hugging Face Hub CLI authentication or the recommended GitHub CLI workflow for IsaacLab-Imitation datasets, pushes, PRs, and CI checks.
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استنادا إلى تصنيف SOC المهني
| name | hub-cli-setup |
| description | Use when setting up Hugging Face Hub CLI authentication or the recommended GitHub CLI workflow for IsaacLab-Imitation datasets, pushes, PRs, and CI checks. |
Use the repo-owned Pixi environments. Hugging Face CLI support lives in the
lerobot environment, while GitHub CLI support lives in the default
environment.
# Hugging Face Hub CLI for LeRobot dataset access. Use hf, not huggingface-cli.
pixi run -e lerobot hf auth login
pixi run -e lerobot hf auth whoami
# GitHub CLI is recommended for branch, push, PR, and CI workflows.
pixi run gh auth login
pixi run gh auth setup-git --hostname github.com
pixi run gh auth status
# Optional: only for direct git push/pull to https://huggingface.co.
# This uses Git's plaintext store helper, scoped to Hugging Face only.
git config --global credential.https://huggingface.co.helper store
# If you are already logged in:
pixi run -e lerobot hf auth list
TOKEN_NAME=home-ubuntu
pixi run -e lerobot hf auth switch --token-name "$TOKEN_NAME" --add-to-git-credential
# If you are not logged in yet:
pixi run -e lerobot hf auth login --add-to-git-credential
# Remove the Hugging Face-scoped helper later if you no longer want it.
git config --global --unset credential.https://huggingface.co.helper
BONES-SEED dataset workflow for this IsaacLab-Imitation repo, including Hugging Face access, Skynet data paths, metadata counts, G1 archive layout, trajectory shortlists, CSV extraction, G1 joint-order validation, root/unit conversion, NPZ export, manifest/language sidecar generation, and MiniLM language embeddings. Use when the user mentions BONES-SEED, bones seed, bones-studio/seed, G1 CSV/NPZ conversion, language-conditioned planner dataset prep, or dataset metadata/joint-order issues.
Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.
Skynet Slurm job workflow for this IsaacLab-Imitation repo, including ssh access, scheduler commands, Apptainer/Pixi runner selection, environment files, log monitoring, cancellation, and safety checks. Use when the user mentions Skynet, sky1, wu-lab, Slurm submissions on Skynet, Apptainer on Skynet compute nodes, or asks to submit/monitor/cancel IsaacLab-Imitation jobs on Skynet.