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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/mosahary%2Fgemma-4-12b-it-qat-abliterated" 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-00005-of-00007.safetensors | 3.72 GB | 1cf4aa74 | download |
| model-00004-of-00007.safetensors | 3.71 GB | 4f8ee4b7 | download |
| model-00003-of-00007.safetensors | 3.68 GB | 8420a52f | download |
| model-00006-of-00007.safetensors | 3.67 GB | 8450445e | download |
| model-00001-of-00007.safetensors | 3.64 GB | cfe50ebb | download |
| model-00002-of-00007.safetensors | 3.63 GB | 517adc7d | download |
| model-00007-of-00007.safetensors | 236 MB | c0cee828 | download |
| tokenizer.json | 30.7 MB | cc8d3a0c | download |
| model.safetensors.index.json | 64.8 KB | 3eb61094 | download |
| chat_template.jinja | 18.5 KB | e929d662 | download |
| tokenizer_config.json | 6.76 KB | f39f0bea | download |
| config.json | 4.92 KB | 94eaf13d | download |
| .gitattributes | 1.53 KB | 52373fe2 | download |
| processor_config.json | 1.35 KB | b889adcd | download |
| README.md | 594 B | ac72cac6 | download |
| generation_config.json | 260 B | 02716c09 | download |
base_model: unsloth/gemma-4-12B-it-qat-q4_0-unquantized
tags:
This gemma4_unified model was trained 2x faster with Unsloth
Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.