Is Transformers Safe?
Yes, Transformers is safe to use. Transformers is a Python package with a Nerq Trust Score of 87.0/100 (A), based on 3 independent data dimensions. It is recommended for production use. Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-24. Machine-readable data (JSON).
Is Transformers safe?
YES — Transformers has a Nerq Trust Score of 87.0/100 (A). It meets Nerq's trust threshold with strong signals across security, maintenance, and community adoption. Recommended for production use — review the full report below for specific considerations.
Trust Score Breakdown
Key Findings
Details
| Author | The Hugging Face team (past and future) with the help of all our contributors (https://github.com/huggingface/transformers/graphs/contributors) |
| Category | pypi |
| Source | N/A |
Transformers Across Platforms
Same developer/company in other registries:
Safety Guide: Transformers
What is Transformers?
Transformers is a Python package — Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training..
How to Verify Safety
Run pip audit or safety check. Review on PyPI for download stats.
You can also check the trust score via API: GET /v1/preflight?target=transformers
Key Safety Concerns for Python packages
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Trust Assessment
Transformers has a Nerq Trust Score of 81/100 (A-) and meets Nerq trust threshold. This score is based on automated analysis of security, maintenance, community, and quality signals.
Key Takeaways
- Transformers has a Trust Score of 81/100 (A-).
- Recommended for use — passes trust threshold.
- Always verify independently using the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Privacy | 80/100 |
| Reliability | 90/100 |
| Transparency | 85/100 |
| Maintenance | 60/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Transformers collect?
Transformers is a Python package maintained by The Hugging Face team (past and future) with the help of all our contributors (https://github.com/huggingface/transformers/graphs/contributors). It receives approximately 29,252,908 weekly downloads. Licensed under Apache 2.0 License.
As a development package, Transformers does not directly collect end-user personal data. However, applications built with it may collect data depending on implementation. Privacy score: 80/100.
Review the package's dependencies for potential supply chain risks. Run your package manager's audit command regularly.
Full analysis: Transformers Privacy Report · Privacy review
Is Transformers secure?
Security score: 90/100. Transformers has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
Licensed under Apache 2.0 License, allowing code inspection. Open-source packages allow independent security review of the source code.
Run your package manager's audit command (`npm audit`, `pip audit`, `cargo audit`) to check for known vulnerabilities in your dependency tree.
Full analysis: Transformers Security Report
Transformers across platforms
Same developer/company in other registries:
How we calculated this score
Transformers's trust score of 87.0/100 (A) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), privacy (80/100), reliability (90/100), transparency (85/100), maintenance (60/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 23 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
This page was last reviewed on March 24, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
Is Transformers safe to use?
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What are safer alternatives to Transformers?
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Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.