Hugging Face / skills/huggingface-community-evals/SKILL.md
Hugging Face Community Evals
Runs benchmark evaluations of Hub models locally with inspect-ai or lighteval, starting from small smoke tests.
Source reviewed · reviewed · Named sources were inspected. No runtime results are established by this label.
01 / Task fit
Where it may help.
These are intended uses indicated by the upstream material. They are not measured outcomes.
- Local benchmark runs on open models
- Choosing an inference backend for evaluation
What it is
This skill helps an agent evaluate models from the Hugging Face Hub on local hardware or through Inference Providers. It chooses between inspect-ai and lighteval, picks an inference backend (vLLM, Transformers or accelerate), and starts with a small sample before a full run. It stops at local runs and hands off remote jobs and result publishing to other skills.
Why you might use it
Use it when you're comparing open models for a task and want standard benchmark numbers from your own run. For business tasks, a small set of your own test cases usually tells you more than public benchmarks.
Put it in context.
Illustrative requests and outputs to review. These examples are separate from the recorded evaluation below.
Smoke-test a model
Example request
Run a 20-sample MMLU smoke test on meta-llama/Llama-3.2-1B using inspect-ai through Inference Providers.
What to look for. A small benchmark result and the command used.
Before you rely on it. Twenty samples is a smoke test, not a score. Don't compare models on it.
Compare two small models on GPU
Example request
Run gsm8k with 50 samples on two models using vLLM, and report both scores with the same settings.
What to look for. Two scores from matched settings.
Before you rely on it. Benchmark scores may not reflect your use case. Add your own test cases before choosing.
02 / Setup & access
What it asks of your environment.
Requirements
- uv, the bundled Python scripts, and an HF_TOKEN for gated or private models.
- A local GPU for vLLM or Transformers runs, or Inference Providers for the lighter path.
Permissions & data access
- Runs local scripts that download models and datasets.
- Uses your Hugging Face token. The provider path sends prompts to inference providers.
Instructions alone do not enforce a sandbox. The agent host, connected tools and approvals determine what the skill can actually read, change or send.
03 / Things to check
Security concerns & practical limits.
These concerns follow from the reviewed sources. They describe possible exposure or required review; they are not confirmed vulnerabilities.
Review before use
Remote code flag
Examples use --trust-remote-code for some models, which runs code from the model repository. Only use it for models you trust.
Limits and nuances
- Source review of SKILL.md and the repository license only. The three bundled scripts and usage examples were not reviewed or run.
- No model was evaluated. No benchmark result is claimed.
04 / Review record
What we checked. What’s still open.
Recorded review scope
- skills/huggingface-community-evals/SKILL.md
- LICENSE
Not tested or established
- Source review of SKILL.md and the repository license only. The three bundled scripts and usage examples were not reviewed or run.
- No model was evaluated. No benchmark result is claimed.
- Review date
- Source revision
c3ff942be3e07116b475253f0a8fc4f54682c1a8- Our relationship
- Explored. Investigated through the recorded review. No use or replication is claimed.
Upstream content can change after review. A repository revision identifies source scope; it does not prove that every script, dependency or runtime behavior was tested. How freshness is handled.
Recorded evaluation / Source review
Results with their limits attached.
Completed 4 bounded source checks on the pinned entrypoint and license. No skill workflow was executed.
- Passed
- 4
- Failed
- 0
- Total recorded
- 4
These counts refer to the cases in this report. They are not a benchmark against other skills. A source review does not establish runtime behavior.
Read the evidence reportThe report provides the case definitions, observations and baseline scope. Missing baselines or untested behaviors remain limitations.
Recorded environment
- Pinned public UTF-8 sources fetched from raw.githubusercontent.com at the recorded commit and hashed with SHA-256.
- Linux; Python 3.13.5 source-condition check. No account, credentials, private documents or live business data.
Recorded commands (2)
Commands document this evaluation. They are not setup instructions for your environment.
Read each pinned file listed in sourceManifest.python3 r6_skills.py: check each recorded source condition and reconcile report counts.Findings from this evaluation
Needs attention
Remote code flag
Examples use --trust-remote-code for some models, which runs code from the model repository. Only use it for models you trust.
Observation
Clear boundary
The skill states what it does not cover, including remote jobs and publishing results.
Evaluation limitations
- Source review of SKILL.md and the repository license only. The three bundled scripts and usage examples were not reviewed or run.
- No model was evaluated. No benchmark result is claimed.
05 / Reuse & discovery
License, attribution & popularity.
Apache-2.0
Apache-2.0 license text inspected at this revision. Keep the license and any NOTICE when redistributing covered files. The services and accounts the skill uses have their own terms.
Why it is in this collection
GitHub displayed 11,182 stars for the huggingface/skills repository on the observation date. Repository-wide; not individual skill usage, quality or safety.
11,182 repository stars
- Scope
- Entire huggingface/skills repository, not this individual skill
- Observed
- Time window
- Snapshot observed 2026-10-19
Popularity and inclusion do not establish quality, compatibility or security. Counts belong to their named metric and date; they are not a current ranking.
06 / Follow the evidence
Go to the original.
- Pinned skill instructions github.com
- Pinned license github.com
- Repository (dated star count) github.com
IonBin’s source notes are independent assessments. Upstream authors retain their work and attribution. This page does not install or execute the skill.