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Trust & integrity
Full report- Maintenance
- Active (11d since push)
- As of today · Source: github_public_v1
- Provenance
- Not a fork · Organization account
- As of today · Source: github_public_v1
- Security (OSV)
- No lockfile
- As of today · Source: none
Public GitHub metadata and optional OSV dependency scans. Signals, not a guarantee. Trust methodology.
Backing
Company and funding context for Hugging Face. Display-only - not part of trust score or organic ranking.
- Company
- Hugging Face·GitHub org profile·today
- Employees
- 160·Wikidata (P1128 employees)·today
- Funding
- $235,000,000 (2023-08)·GraphCanon curated seed (public press)·today
- Commercial model
- OSS + managed cloud·GraphCanon curated seed·today
Overview
Lighteval provides a comprehensive set of tools and frameworks to evaluate the performance of language models (LLMs) on different computing platforms or backend infrastructures.
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Jul 12, 2026
- Languages
- python
Source: github.language+pyproject.toml · Jul 12, 2026
Categories
Graph entities
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
⚡️ Installation
Note: lighteval is currently completely untested on Windows, and we don't support it yet. (Should be fully functional on Mac/Linux)
pip install lighteval
Lighteval allows for many extras when installing, see here for a complete list.
If you want to push results to the Hugging Face Hub, add your access token as an environment variable:
hf auth login