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Below is the per-quantization compatibility for this model.
curl -H "Authorization: Bearer $ABL_KEY" \
"https://abliteration.org/api/v1/models/Nexesenex%2Fpankajmathur_orca_mini_v9_6_1B-instruct-Abliterated-LPL" primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.
| model.safetensors | 2.30 GB | ba1813d5 | download |
| tokenizer.json | 16.4 MB | 6b9e4e7f | download |
| tokenizer_config.json | 51.9 KB | 3a2e694d | download |
| .gitattributes | 1.53 KB | 52373fe2 | download |
| config.json | 972 B | 57582a8c | download |
| special_tokens_map.json | 477 B | 2969fb88 | download |
| README.md | 361 B | a3b1e84c | download |
| generation_config.json | 196 B | c432ed82 | download |
license: llama3.2
base_model:
pankajmathur/orca_mini_v9_6_1B-Instruct abliterated with https://github.com/Orion-zhen/abliteration and the LPL (layer per layer) technique of Undi95.
For this model, it provokes a lesser alteration of its capacities than a single pass abliteration over the whole model.
The author's README evolved over time. Click a version to see its content at that point.
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