Instructions to use nirmanpatel/llama-risk-compliant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nirmanpatel/llama-risk-compliant with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nirmanpatel/llama-risk-compliant", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use nirmanpatel/llama-risk-compliant with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for nirmanpatel/llama-risk-compliant to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for nirmanpatel/llama-risk-compliant to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for nirmanpatel/llama-risk-compliant to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="nirmanpatel/llama-risk-compliant", max_seq_length=2048, )
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README.md
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tags:
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- unsloth
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- trl
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- lora
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- ethics
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- compliance
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- gdpr
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- transformers
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- gradio
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- safetensors
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model-index:
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- name: PrismAI-Llama-Risk-Monitor
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results: []
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- **Method:** Supervised Fine-Tuning (SFT)
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## Use Case Examples
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**Input:** "I'm sending Sarah's home address (123 Maple St) to the external marketing vendor."
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**Output:** "🛡️ Risk Detected: PII exposure. Ensure Sarah's consent is documented and use a secure encrypted channel for home address sharing."
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## How to use
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```python
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tags:
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- unsloth
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- trl
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- ethics
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- compliance
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- gdpr
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- transformers
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- safetensors
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- Gradio
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- LoRA
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model-index:
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- name: PrismAI-Llama-Risk-Monitor
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results: []
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- **Method:** Supervised Fine-Tuning (SFT)
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## Use Case Examples
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- **Input:** "I'm sending Sarah's home address (123 Maple St) to the external marketing vendor."
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- **Output:** "🛡️ Risk Detected: PII exposure. Ensure Sarah's consent is documented and use a secure encrypted channel for home address sharing."
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## How to use
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```python
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