Localized reading guide
huggingface-bestPurpose, usage and source
Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.
Source retrieved:
- Source repository
- huggingface/skills
- SKILL.md
skills/huggingface-best/SKILL.md- Repository stars
- 11,241
- Repository updated
- 2026-10-30
- Categories
- Other
- Last collected
License: Apache-2.0
Workflow excerpts are reading aids, not executable instructions from Codez. No third-party Skill was run to produce this page.
The purpose and workflow passages below are upstream material, organized and translated for reading. They are distinct from the separately labeled Codez editorial analysis.
What this Skill does
Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.
How the upstream workflow works
Step 1: Parse the request
Extract from the user's message: Task: what they want the model to do (coding, math/reasoning, chat, OCR, RAG/retrieval, speech recognition, image classification, multimodal, agents, etc.) Device: hardware constraints (MacBook M-series 8/16/32/64GB unified memory, RTX GPU with VRAM amount, CPU-only, cloud/no constraint, etc.) If device is not mentioned, skip filtering entirely and return the highest-performing models regardless of size. If the task is genuinely ambiguous, ask one clarifying question.
Upstream passage · L22 ↗Step 2: Find relevant benchmark datasets
Fetch the full list of official HF benchmarks: Read the returned list and select the datasets most relevant to the user's task — match on dataset id, tags, and description. Use your judgment; don't limit yourself to 2-3. Aim for comprehensive coverage: if 5 benchmarks clearly cover the task, use all 5.
Upstream passage · L41 ↗Step 3: Fetch top models from leaderboards
For each selected benchmark dataset: Collect model IDs and scores across all benchmarks. If a leaderboard returns an error (404, 401, etc.), skip it and note it in the output.
Upstream passage · L54 ↗curl -s -H "Authorization: Bearer $(cat ~/.cache/huggingface/token)" \
"https://huggingface.co/api/datasets?filter=benchmark:official&limit=500" | jq '[.[] | {id, tags, description}]'Requirements and setup
No short requirements passage was selected from this file. This does not mean the Skill has no dependencies. Check the repository setup instructions and referenced files.
Limits and quality checks
No separate limits passage was selected from this file. This does not mean the Skill is safe for every input or environment. Review the complete source and validate your own result.
Start with a safe trial
- Check the supported host and the repository installation instructions. Keep the Skill directory and its referenced scripts, assets and documentation together; SKILL.md alone may omit dependencies.
- Give the agent your real input, desired output and acceptance criteria. Invocation syntax and available tools depend on the host; this site does not assume a universal install command.
- Try the source workflow in a disposable project or on a copy. Review operations that change files, remote services or billable resources before allowing them.
- Validate the output against the source quality checks and your own requirements. A successful trigger or a high repository Star count does not establish a correct result.
Read further in the source
Related Skills
Translation and scope
This reading guide selects passages from the pinned upstream SKILL.md. Translation is assisted. It is not a complete manual or a claim of tested compatibility. Read the original and its referenced files before use.
This introduction refers to the pinned version below; current repository activity and collection time are shown separately.
- Pinned source
- Read the original ↗
- Source retrieved
- Source commit
fabc634a893f62ad5c2039830397efa35fa62715- Source SHA-256
4566c02cb6da804dcc434b6b4d48a1895e937157cdaec4ec4c523a2f97cf16d0