Is Watashiha Llama 2 13B Ogiri Sft Safe? — Trust Score: 55.6/100

According to Nerq's independent analysis of Watashiha-Llama-2-13B-Ogiri-sft, this AI tool has a trust score of 55.6 out of 100, earning a D grade. With 13 stars on huggingface_full, it is below the recommended threshold of 70. Compliance: 87/100 across 52 jurisdictions. Data sourced from 13+ independent signals including GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-18. Machine-readable data (JSON).

Watashiha-Llama-2-13B-Ogiri-sft has a Nerq Trust Score of 55.6/100 (D). Not yet Nerq Verified (requires 70+). Its strongest signal is compliance (87/100). Compliance: 45 of 52 jurisdictions. Last verified: 2026-03-18.

Is Watashiha Llama 2 13B Ogiri Sft safe?

CAUTION — Watashiha Llama 2 13B Ogiri Sft has a Nerq Trust Score of 55.6/100 (D). It has moderate trust signals but shows some areas of concern that warrant attention. Suitable for development use — review security and maintenance signals before production deployment.

55.6
out of 100
D AI tool huggingface_full

Trust Assessment

Moderate — Watashiha-Llama-2-13B-Ogiri-sft shows mixed trust signals. Some areas are strong while others could be improved. We recommend reviewing the full KYA (Know Your Agent) report before integrating it into production workflows.

Trust Signal Breakdown

Compliance
87
Regulatory alignment. EU AI Act risk class: N/A.
Maintenance
0
Update frequency, issue responsiveness, active development.
Documentation
0
README quality, API docs, usage examples.
Popularity
0
Community adoption. 13 stars on huggingface_full.

Details

Authorwatashiha
CategoryAI tool
Stars13
Sourcehttps://huggingface.co/watashiha/Watashiha-Llama-2-13B-Ogiri-sft
Protocolshuggingface_hub

Regulatory Compliance

EU AI Act Risk ClassNot assessed
Compliance Score87/100
JurisdictionsAssessed across 52 jurisdictions

Popular Alternatives in AI tool

openclaw/openclaw
84.3/100 · A
github
AUTOMATIC1111/stable-diffusion-webui
69.3/100 · C
github
f/prompts.chat
69.3/100 · C
github
microsoft/generative-ai-for-beginners
71.8/100 · B
github
Comfy-Org/ComfyUI
71.8/100 · B
github

Community Reviews

No reviews yet. Be the first to review Watashiha-Llama-2-13B-Ogiri-sft.

What Is Watashiha Llama 2 13B Ogiri Sft?

Watashiha Llama 2 13B Ogiri Sft is a AI tool in the AI tool category. A large language model-based automation tool.

As of March 2026, Watashiha Llama 2 13B Ogiri Sft is available on huggingface_full, making it an emerging tool in the AI ecosystem. But popularity alone does not equal safety — which is why Nerq independently analyzes every tool across 13+ trust signals.

How Nerq Assesses Watashiha Llama 2 13B Ogiri Sft's Safety

Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Watashiha Llama 2 13B Ogiri Sft performs in each:

The overall Trust Score of 55.6/100 (D) reflects the weighted combination of these signals. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.

Who Should Use Watashiha Llama 2 13B Ogiri Sft?

Watashiha Llama 2 13B Ogiri Sft is designed for:

Risk guidance: Watashiha Llama 2 13B Ogiri Sft is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.

How to Verify Watashiha Llama 2 13B Ogiri Sft's Safety Yourself

While Nerq provides automated trust analysis, we recommend these additional steps before adopting any AI tool:

  1. Check the source code — Review the repository security policy, open issues, and recent commits for signs of active maintenance.
  2. Scan dependencies — Use tools like npm audit, pip-audit, or snyk to check for known vulnerabilities in Watashiha Llama 2 13B Ogiri Sft's dependency tree.
  3. Review permissions — Understand what access Watashiha Llama 2 13B Ogiri Sft requires. AI tools should follow the principle of least privilege.
  4. Test in isolation — Run Watashiha Llama 2 13B Ogiri Sft in a sandboxed environment before granting access to production data or systems.
  5. Monitor continuously — Use Nerq's API to set up automated trust checks: GET nerq.ai/v1/preflight?target=Watashiha-Llama-2-13B-Ogiri-sft
  6. Review the license — Confirm that Watashiha Llama 2 13B Ogiri Sft's license is compatible with your intended use case. Pay attention to restrictions on commercial use, redistribution, and derivative works. Some AI tools use dual licensing or have separate terms for enterprise customers that differ from the open-source license.
  7. Check community signals — Look at the project's issue tracker, discussion forums, and social media presence. A healthy community actively reports bugs, contributes fixes, and discusses security concerns openly. Low community engagement may indicate limited peer review of the codebase.

Common Safety Concerns with Watashiha Llama 2 13B Ogiri Sft

When evaluating whether Watashiha Llama 2 13B Ogiri Sft is safe, consider these category-specific risks:

Data handling

Understand how Watashiha Llama 2 13B Ogiri Sft processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.

Dependency security

Check Watashiha Llama 2 13B Ogiri Sft's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.

Update frequency

Regularly check for updates to Watashiha Llama 2 13B Ogiri Sft. Security patches and bug fixes are only effective if you're running the latest version.

Third-party integrations

If Watashiha Llama 2 13B Ogiri Sft connects to external APIs or services, each integration point is a potential attack surface. Audit all third-party connections, verify that data shared with external services is minimized, and ensure that integration credentials are rotated regularly.

License and IP compliance

Verify that Watashiha Llama 2 13B Ogiri Sft's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Watashiha Llama 2 13B Ogiri Sft in violation of its license can expose your organization to legal liability.

Best Practices for Using Watashiha Llama 2 13B Ogiri Sft Safely

Whether you're an individual developer or an enterprise team, these practices will help you get the most from Watashiha Llama 2 13B Ogiri Sft while minimizing risk:

Conduct regular audits

Periodically review how Watashiha Llama 2 13B Ogiri Sft is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.

Keep dependencies updated

Ensure Watashiha Llama 2 13B Ogiri Sft and all its dependencies are running the latest stable versions to benefit from security patches.

Follow least privilege

Grant Watashiha Llama 2 13B Ogiri Sft only the minimum permissions it needs to function. Avoid granting admin or root access.

Monitor for security advisories

Subscribe to Watashiha Llama 2 13B Ogiri Sft's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.

Document usage policies

Create and maintain a clear policy for how Watashiha Llama 2 13B Ogiri Sft is used within your organization, including data handling guidelines and acceptable use cases.

When Should You Avoid Watashiha Llama 2 13B Ogiri Sft?

Even promising tools aren't right for every situation. Consider avoiding Watashiha Llama 2 13B Ogiri Sft in these scenarios:

For each scenario, evaluate whether Watashiha Llama 2 13B Ogiri Sft's trust score of 55.6/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.

How Watashiha Llama 2 13B Ogiri Sft Compares to Industry Standards

Nerq indexes over 204,000 AI agents and tools across dozens of categories. Among AI tool tools, the average Trust Score is 62/100. Watashiha Llama 2 13B Ogiri Sft's score of 55.6/100 is near the category average of 62/100.

This places Watashiha Llama 2 13B Ogiri Sft in line with the typical AI tool tool tool. It meets baseline expectations but does not distinguish itself from peers on trust metrics.

Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate in isolation may actually represent strong performance within a challenging category — or vice versa. Nerq's category-relative analysis helps teams make informed decisions by showing not just absolute quality, but how a tool ranks against its direct peers.

Trust Score History

Nerq continuously monitors Watashiha Llama 2 13B Ogiri Sft and recalculates its Trust Score as new data becomes available. Our scoring engine ingests real-time signals from source repositories, vulnerability databases (NVD, OSV.dev), package registries, and community metrics. When a new CVE is published, a major release ships, or maintenance patterns change, Watashiha Llama 2 13B Ogiri Sft's score is updated within 24 hours.

Historical trust trends reveal whether a tool is improving, stable, or declining over time. A tool that consistently maintains or improves its score demonstrates ongoing commitment to security and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Watashiha Llama 2 13B Ogiri Sft's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=Watashiha-Llama-2-13B-Ogiri-sft&include=history

Nerq retains trust score snapshots at regular intervals, enabling trend analysis across weeks and months. Enterprise users can access detailed historical reports showing how each dimension — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Watashiha Llama 2 13B Ogiri Sft are strengthening or weakening over time.

Watashiha Llama 2 13B Ogiri Sft vs Alternatives

In the AI tool category, Watashiha Llama 2 13B Ogiri Sft scores 55.6/100. There are higher-scoring alternatives available. For a detailed comparison, see:

Key Takeaways

Frequently Asked Questions

Is Watashiha-Llama-2-13B-Ogiri-sft safe to use?
Watashiha-Llama-2-13B-Ogiri-sft has a Nerq Trust Score of 55.6/100, earning a D grade. Moderate — Watashiha-Llama-2-13B-Ogiri-sft shows mixed trust signals. Some areas are strong while others could be improved. We recommend reviewing the full KYA (Know Your Agent) report before integrating it into production workflows. Its strongest signal is compliance (87/100). It has not yet reached the Nerq Verified threshold of 70. Always review the full KYA report before using any AI agent in production.
What is Watashiha-Llama-2-13B-Ogiri-sft's trust score?
Nerq assigns Watashiha-Llama-2-13B-Ogiri-sft a trust score of 55.6 out of 100, with a grade of D. This score is computed from multiple dimensions including security, compliance, maintenance activity, documentation quality, and community adoption (13 stars). Compliance score: 87/100. Scores are updated daily based on the latest publicly available signals.
Are there safer alternatives to Watashiha-Llama-2-13B-Ogiri-sft?
In the AI tool category, higher-rated alternatives include openclaw/openclaw, AUTOMATIC1111/stable-diffusion-webui, f/prompts.chat (scores: 84, 69, 69). Watashiha-Llama-2-13B-Ogiri-sft scores 55.6/100. When choosing between agents, consider your specific requirements for security (N/A), maintenance activity (N/A), and documentation (N/A). Use Nerq's comparison tools or the KYA endpoint for detailed side-by-side analysis.
How often is Watashiha Llama 2 13B Ogiri Sft's safety score updated?
Nerq continuously monitors Watashiha Llama 2 13B Ogiri Sft and updates its trust score as new data becomes available. The system ingests signals from 13+ independent sources including GitHub, NVD (National Vulnerability Database), OSV.dev, OpenSSF Scorecard, and major package registries (npm, PyPI). When a new CVE is disclosed, a dependency is updated, or commit activity changes, the score adjusts automatically. For the most current score, query the Nerq API: GET nerq.ai/v1/preflight?target=Watashiha-Llama-2-13B-Ogiri-sft. The current assessment (55.6/100, D) was last verified on 2026-03-18.
Can I use Watashiha Llama 2 13B Ogiri Sft in a regulated environment?
Watashiha Llama 2 13B Ogiri Sft has not yet reached the Nerq Verified threshold of 70, which means additional due diligence is recommended for regulated environments. Nerq assesses compliance across 52 jurisdictions. Watashiha Llama 2 13B Ogiri Sft has a compliance score of 87/100. For organizations in regulated industries (healthcare, finance, government), we recommend combining the Nerq Trust Score with your internal security review process, vendor risk assessment, and legal compliance check before deployment.

Add This Badge to YOUR Project

Nerq Trust Score for Watashiha-Llama-2-13B-Ogiri-sft

Show users your project is trusted. Add this badge to your README:

[![Nerq Trust Score](https://nerq.ai/badge/Watashiha-Llama-2-13B-Ogiri-sft)](https://nerq.ai/safe/tashi)

Click to copy. Works on GitHub, GitLab, and any markdown renderer.

Scan your project
pip install nerq && nerq scan

Scans all dependencies for trust scores and security issues.

Integrate trust checks
curl nerq.ai/v1/preflight?target=tashi
API docs →
Improve this score
See recommendations →
Verify any agent
Browse AI tool
All agents · MCP servers · Compare · Gateway

Related Safety Checks

Is Cursor safe? Is ChatGPT safe? Is Claude safe? Is Windsurf safe? Is Bolt safe? Is Cline safe? Is GitHub Copilot safe? Is Gemini safe? Is Ollama safe? Is LangChain safe? Is OpenAI safe? Is n8n safe? Is ComfyUI safe? Is CrewAI safe? Is AutoGPT safe? Is Devin safe? Is Continue safe? Is LlamaIndex safe? Is Hugging Face safe? Is Stable Diffusion safe?

Disclaimer: Nerq trust scores are automated assessments based on publicly available signals. They are not endorsements or guarantees. Always conduct your own due diligence.

Also explore

Nerq Trust Protocol AI Compliance Hub Know Your Agent Crypto Vitality Rankings Crash Watch: Live Alerts Real-Time Token Scanner