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| model-00002-of-00004.safetensors | 4.66 GB | bbc6d407 | download |
| model-00001-of-00004.safetensors | 4.63 GB | 7992c5bc | download |
| model-00003-of-00004.safetensors | 4.58 GB | daf414ff | download |
| model-00004-of-00004.safetensors | 1.09 GB | 013bc9e3 | download |
| tokenizer.json | 16.4 MB | 6b9e4e7f | download |
| tokenizer_config.json | 54.2 KB | f993d1de | download |
| model.safetensors.index.json | 23.4 KB | 0fd8120f | download |
| .gitattributes | 1.53 KB | 52373fe2 | download |
| config.json | 927 B | 2c358ea8 | download |
| README.md | 411 B | e2263fdd | download |
| special_tokens_map.json | 325 B | b43be966 | download |
| generation_config.json | 234 B | 06c4ff6a | download |
license: llama3.1
base_model:
Decensored using a custom training script guided by activations, similar to ablation/"abliteration" scripts but not exactly the same approach.
I've found this effect to be stronger than most abliteration scripts, so please use responsibly etc etc.
The training script is released under the MIT license: https://github.com/nkpz/DeLMAT
The author's README evolved over time. Click a version to see its content at that point.
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