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* docs: deep audit — fix stale config keys, missing commands, and registry drift Cross-checked ~80 high-impact docs pages (getting-started, reference, top-level user-guide, user-guide/features) against the live registries: hermes_cli/commands.py COMMAND_REGISTRY (slash commands) hermes_cli/auth.py PROVIDER_REGISTRY (providers) hermes_cli/config.py DEFAULT_CONFIG (config keys) toolsets.py TOOLSETS (toolsets) tools/registry.py get_all_tool_names() (tools) python -m hermes_cli.main <subcmd> --help (CLI args) reference/ - cli-commands.md: drop duplicate hermes fallback row + duplicate section, add stepfun/lmstudio to --provider enum, expand auth/mcp/curator subcommand lists to match --help output (status/logout/spotify, login, archive/prune/ list-archived). - slash-commands.md: add missing /sessions and /reload-skills entries + correct the cross-platform Notes line. - tools-reference.md: drop bogus '68 tools' headline, drop fictional 'browser-cdp toolset' (these tools live in 'browser' and are runtime-gated), add missing 'kanban' and 'video' toolset sections, fix MCP example to use the real mcp_<server>_<tool> prefix. - toolsets-reference.md: list browser_cdp/browser_dialog inside the 'browser' row, add missing 'kanban' and 'video' toolset rows, drop the stale '38 tools' count for hermes-cli. - profile-commands.md: add missing install/update/info subcommands, document fish completion. - environment-variables.md: dedupe GMI_API_KEY/GMI_BASE_URL rows (kept the one with the correct gmi-serving.com default). - faq.md: Anthropic/Google/OpenAI examples — direct providers exist (not just via OpenRouter), refresh the OpenAI model list. getting-started/ - installation.md: PortableGit (not MinGit) is what the Windows installer fetches; document the 32-bit MinGit fallback. - installation.md / termux.md: installer prefers .[termux-all] then falls back to .[termux]. - nix-setup.md: Python 3.12 (not 3.11), Node.js 22 (not 20); fix invalid 'nix flake update --flake' invocation. - updating.md: 'hermes backup restore --state pre-update' doesn't exist — point at the snapshot/quick-snapshot flow; correct config key 'updates.pre_update_backup' (was 'update.backup'). user-guide/ - configuration.md: api_max_retries default 3 (not 2); display.runtime_footer is the real key (not display.runtime_metadata_footer); checkpoints defaults enabled=false / max_snapshots=20 (not true / 50). - configuring-models.md: 'hermes model list' / 'hermes model set ...' don't exist — hermes model is interactive only. - tui.md: busy_indicator -> tui_status_indicator with values kaomoji|emoji|unicode|ascii (not kawaii|minimal|dots|wings|none). - security.md: SSH backend keys (TERMINAL_SSH_HOST/USER/KEY) live in .env, not config.yaml. - windows-wsl-quickstart.md: there is no 'hermes api' subcommand — the OpenAI-compatible API server runs inside hermes gateway. user-guide/features/ - computer-use.md: approvals.mode (not security.approval_level); fix broken ./browser-use.md link to ./browser.md. - fallback-providers.md: top-level fallback_providers (not model.fallback_providers); the picker is subcommand-based, not modal. - api-server.md: API_SERVER_* are env vars — write to per-profile .env, not 'hermes config set' which targets YAML. - web-search.md: drop web_crawl as a registered tool (it isn't); deep-crawl modes are exposed through web_extract. - kanban.md: failure_limit default is 2, not '~5'. - plugins.md: drop hard-coded '33 providers' count. - honcho.md: fix unclosed quote in echo HONCHO_API_KEY snippet; document that 'hermes honcho' subcommand is gated on memory.provider=honcho; reconcile subcommand list with actual --help output. - memory-providers.md: legacy 'hermes honcho setup' redirect documented. Verified via 'npm run build' — site builds cleanly; broken-link count went from 149 to 146 (no regressions, fixed a few in passing). * docs: round 2 audit fixes + regenerate skill catalogs Follow-up to the previous commit on this branch: Round 2 manual fixes: - quickstart.md: KIMI_CODING_API_KEY mentioned alongside KIMI_API_KEY; voice-mode and ACP install commands rewritten — bare 'pip install ...' doesn't work for curl-installed setups (no pip on PATH, not in repo dir); replaced with 'cd ~/.hermes/hermes-agent && uv pip install -e ".[voice]"'. ACP already ships in [all] so the curl install includes it. - cli.md / configuration.md: 'auxiliary.compression.model' shown as 'google/gemini-3-flash-preview' (the doc's own claimed default); actual default is empty (= use main model). Reworded as 'leave empty (default) or pin a cheap model'. - built-in-plugins.md: added the bundled 'kanban/dashboard' plugin row that was missing from the table. Regenerated skill catalogs: - ran website/scripts/generate-skill-docs.py to refresh all 163 per-skill pages and both reference catalogs (skills-catalog.md, optional-skills-catalog.md). This adds the entries that were genuinely missing — productivity/teams-meeting-pipeline (bundled), optional/finance/* (entire category — 7 skills: 3-statement-model, comps-analysis, dcf-model, excel-author, lbo-model, merger-model, pptx-author), creative/hyperframes, creative/kanban-video-orchestrator, devops/watchers, productivity/shop-app, research/searxng-search, apple/macos-computer-use — and rewrites every other per-skill page from the current SKILL.md. Most diffs are tiny (one line of refreshed metadata). Validation: - 'npm run build' succeeded. - Broken-link count moved 146 -> 155 — the +9 are zh-Hans translation shells that lag every newly-added skill page (pre-existing pattern). No regressions on any en/ page.
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| title | sidebar_label | description |
|---|---|---|
| Huggingface Hub — HuggingFace hf CLI: search/download/upload models, datasets | Huggingface Hub | HuggingFace hf CLI: search/download/upload models, datasets |
{/* This page is auto-generated from the skill's SKILL.md by website/scripts/generate-skill-docs.py. Edit the source SKILL.md, not this page. */}
Huggingface Hub
HuggingFace hf CLI: search/download/upload models, datasets.
Skill metadata
| Source | Bundled (installed by default) |
| Path | skills/mlops/huggingface-hub |
| Version | 1.0.0 |
| Author | Hugging Face |
| License | MIT |
| Platforms | linux, macos, windows |
Reference: full SKILL.md
:::info The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active. :::
Hugging Face CLI (hf) Reference Guide
The hf command is the modern command-line interface for interacting with the Hugging Face Hub, providing tools to manage repositories, models, datasets, and Spaces.
IMPORTANT: The
hfcommand replaces the now deprecatedhuggingface-clicommand.
Quick Start
- Installation:
curl -LsSf https://hf.co/cli/install.sh | bash -s - Help: Use
hf --helpto view all available functions and real-world examples. - Authentication: Recommended via
HF_TOKENenvironment variable or the--tokenflag.
Core Commands
General Operations
hf download REPO_ID: Download files from the Hub.hf upload REPO_ID: Upload files/folders (recommended for single-commit).hf upload-large-folder REPO_ID LOCAL_PATH: Recommended for resumable uploads of large directories.hf sync: Sync files between a local directory and a bucket.hf env/hf version: View environment and version details.
Authentication (hf auth)
login/logout: Manage sessions using tokens from huggingface.co/settings/tokens.list/switch: Manage and toggle between multiple stored access tokens.whoami: Identify the currently logged-in account.
Repository Management (hf repos)
create/delete: Create or permanently remove repositories.duplicate: Clone a model, dataset, or Space to a new ID.move: Transfer a repository between namespaces.branch/tag: Manage Git-like references.delete-files: Remove specific files using patterns.
Specialized Hub Interactions
Datasets & Models
- Datasets:
hf datasets list,info, andparquet(list parquet URLs). - SQL Queries:
hf datasets sql SQL— Execute raw SQL via DuckDB against dataset parquet URLs. - Models:
hf models listandinfo. - Papers:
hf papers list— View daily papers.
Discussions & Pull Requests (hf discussions)
- Manage the lifecycle of Hub contributions:
list,create,info,comment,close,reopen, andrename. diff: View changes in a PR.merge: Finalize pull requests.
Infrastructure & Compute
- Endpoints: Deploy and manage Inference Endpoints (
deploy,pause,resume,scale-to-zero,catalog). - Jobs: Run compute tasks on HF infrastructure. Includes
hf jobs uvfor running Python scripts with inline dependencies andstatsfor resource monitoring. - Spaces: Manage interactive apps. Includes
dev-modeandhot-reloadfor Python files without full restarts.
Storage & Automation
- Buckets: Full S3-like bucket management (
create,cp,mv,rm,sync). - Cache: Manage local storage with
list,prune(remove detached revisions), andverify(checksum checks). - Webhooks: Automate workflows by managing Hub webhooks (
create,watch,enable/disable). - Collections: Organize Hub items into collections (
add-item,update,list).
Advanced Usage & Tips
Global Flags
--format json: Produces machine-readable output for automation.-q/--quiet: Limits output to IDs only.
Extensions & Skills
- Extensions: Extend CLI functionality via GitHub repositories using
hf extensions install REPO_ID. - Skills: Manage AI assistant skills with
hf skills add.