Instructions to use itsalissonsilva/Restriction-Learning-Experiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use itsalissonsilva/Restriction-Learning-Experiment with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-3-1b-it") model = PeftModel.from_pretrained(base_model, "itsalissonsilva/Restriction-Learning-Experiment") - Notebooks
- Google Colab
- Kaggle
Release exact Forensics restriction adapter with public weights, layer/strength evidence, controls and Gemma terms
9fbaf4c verified Download NOTICE from itsalissonsilva/Restriction-Learning-Experiment: direct link, hf CLI and curl.
- Browser
- Download file 459 Bytes
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https://huggingface.co/itsalissonsilva/Restriction-Learning-Experiment/resolve/main/NOTICE
- Command line
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hf download hf://itsalissonsilva/Restriction-Learning-Experiment/NOTICE
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curl -L -o NOTICE https://huggingface.co/itsalissonsilva/Restriction-Learning-Experiment/resolve/main/NOTICE
459 Bytes
| Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms | |
| The selective and blanket-refusal adapters were trained by itsalissonsilva on synthetic workspace data. These modified artifacts are subject to the Gemma Terms of Use, including Section 3.2 and the incorporated Prohibited Use Policy. This is not an official Google release or endorsement. All marked-private values in the accompanying experiment are synthetic. | |