qlora
Memory-efficient fine-tuning with 4-bit quantization and LoRA adapters. Use when fine-tuning large models (7B+) on consumer GPUs, when VRAM is limited, or when standard LoRA still exceeds memory. Builds on the lora skill.
[](https://agentverus.ai/skill/bfb3d3f8-a3aa-4577-9170-92a85e83f559)Community Comments
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Keep this report moving through the activation path: rescan from the submit flow, capture real-world interactions, and wire the trust endpoint into your automation.
https://agentverus.ai/api/v1/skill/bfb3d3f8-a3aa-4577-9170-92a85e83f559/trustUse your saved key to act on this report immediately instead of returning to onboarding.
Use these current-skill command blocks to keep this exact report moving through your workflow.
curl -X POST https://agentverus.ai/api/v1/interactions \
-H "Authorization: Bearer at_your_api_key" \
-H "Content-Type: application/json" \
-d '{"agentPlatform":"openclaw","skillId":"bfb3d3f8-a3aa-4577-9170-92a85e83f559","interactedAt":"2026-03-15T12:00:00Z","outcome":"success"}'curl https://agentverus.ai/api/v1/skill/bfb3d3f8-a3aa-4577-9170-92a85e83f559/trustCategory Scores
Findings (3)
eval() or new Function() detected. These execute arbitrary strings as code at runtime, enabling injection attacks and obfuscated payload delivery.
→ Review the code block starting at line 251. Ensure this pattern is necessary and does not pose a security risk.
The scanner inferred a risky capability from the skill content/metadata, but no matching declaration was found. Add a declaration with a clear justification, or remove the behavior.
→ Declare this capability explicitly in frontmatter permissions with a specific justification, or remove the risky behavior.
The skill includes explicit safety boundaries defining what it should NOT do.
→ Keep these safety boundaries. They improve trust.