Downloads · 30 days
0
llama-risk-compliant
nirmanpatel/llama-risk-compliant
llama-risk-compliant is a machine learning model from nirmanpatel. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
This model is a fine-tuned version of Llama-3-8B optimized for Corporate Compliance and Ethical Monitoring.
Access
Public
Updated Jan 4, 2026
Repo size
185 MB
Likes
1
Public
Repo makeup
Click a slice to open those files.
.safetensors168 MB · 91%
At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Jan 4, 2026
- Updated
- Jan 4, 2026
- SHA
- 2fa3c0dc
Base models
Model card
From the Hugging Face model README
PrismAI: Llama-Risk-Complaint
This model is a fine-tuned version of Llama-3-8B optimized for Corporate Compliance and Ethical Monitoring.
Model Description
PrismAI is trained to identify and mitigate risks associated with:
- GDPR Violations: Accidental sharing of PII (Names, Addresses, ID numbers).
- Workplace Ethics: Unconscious bias in hiring or management communication.
- Legal Risks: Improper handling of "Opt-out" lists or internal secrets.
Training Procedure
- Library: Unsloth & PEFT
- Hardware: NVIDIA T4 GPU
- Quantization: 4-bit (bitsandbytes)
- Method: Supervised Fine-Tuning (SFT)
Use Case Examples
- Input: "I'm sending Sarah's home address (123 Maple St) to the external marketing vendor."
- Output: "🛡️ Risk Detected: PII exposure. Ensure Sarah's consent is documented and use a secure encrypted channel for home address sharing."
How to use
from unsloth import FastLanguageModel
model, tokenizer = FastLanguageModel.from_pretrained("nirmanpatel/llama-risk-compliant")
This llama model was trained 2x faster with Unsloth
- Library
- transformers
- License
- apache-2.0
- Created
- Jan 4, 2026
- Updated
- Jan 4, 2026