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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/numen-tech%2FLlama-3.2-1B-Instruct-abliterated-q0f16" primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
| Benchmark | Score | Source |
|---|---|---|
| Entertainment | 0.6 | UGI |
| Hazardous | 0.6 | UGI |
| Natural Intelligence | 6.63 | UGI |
| Political lean | -6.4% | UGI |
| Sensitive-Info | 5.1 | UGI |
| SocPol | 0.3 | UGI |
| UGI | 10.9 | UGI |
| Willingness (10) | 2.2 | UGI |
| W10-Adherence | 0.5 | UGI |
| W10-Direct | 4 | UGI |
| Writing | 13.92 | UGI |
This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.
| params_shard_0.bin | 501 MB | 32d01935 | download |
| params_shard_10.bin | 64.0 MB | 1089e327 | download |
| params_shard_13.bin | 64.0 MB | 159d7598 | download |
| params_shard_16.bin | 64.0 MB | b6fecae8 | download |
| params_shard_19.bin | 64.0 MB | cb34b1a1 | download |
| params_shard_2.bin | 64.0 MB | 64746fce | download |
| params_shard_22.bin | 64.0 MB | 3d02a714 | download |
| params_shard_25.bin | 64.0 MB | 3f9e9435 | download |
| params_shard_28.bin | 64.0 MB | 0e64dec4 | download |
| params_shard_31.bin | 64.0 MB | fc6ca0b3 | download |
| params_shard_34.bin | 64.0 MB | e63b7628 | download |
| params_shard_37.bin | 64.0 MB | 9d02eb69 | download |
| params_shard_4.bin | 64.0 MB | 1b6c2c9a | download |
| params_shard_40.bin | 64.0 MB | dc64681d | download |
| params_shard_43.bin | 64.0 MB | 9e043c0a | download |
| params_shard_46.bin | 64.0 MB | 25475ec1 | download |
| params_shard_7.bin | 64.0 MB | f09f2391 | download |
| params_shard_1.bin | 32.0 MB | 1d833504 | download |
| params_shard_12.bin | 32.0 MB | 4b0b2554 | download |
| params_shard_15.bin | 32.0 MB | 675132cb | download |
| params_shard_18.bin | 32.0 MB | 2524fe8e | download |
| params_shard_21.bin | 32.0 MB | b688cdcb | download |
| params_shard_24.bin | 32.0 MB | 7f431dbc | download |
| params_shard_27.bin | 32.0 MB | 747e4653 | download |
| params_shard_3.bin | 32.0 MB | 0ca63351 | download |
| params_shard_30.bin | 32.0 MB | 8a228f3d | download |
| params_shard_33.bin | 32.0 MB | 0962b167 | download |
| params_shard_36.bin | 32.0 MB | 796fe2a7 | download |
| params_shard_39.bin | 32.0 MB | c4e549ce | download |
| params_shard_42.bin | 32.0 MB | 0c1b5803 | download |
| params_shard_45.bin | 32.0 MB | 32bdc219 | download |
| params_shard_6.bin | 32.0 MB | 7afd50bf | download |
| params_shard_9.bin | 32.0 MB | 37571128 | download |
| params_shard_5.bin | 20.0 MB | 4973a9d2 | download |
| params_shard_11.bin | 20.0 MB | 45d29759 | download |
| params_shard_14.bin | 20.0 MB | 706d803b | download |
| params_shard_17.bin | 20.0 MB | d40e371d | download |
| params_shard_20.bin | 20.0 MB | 08576b73 | download |
| params_shard_23.bin | 20.0 MB | e43b9689 | download |
| params_shard_26.bin | 20.0 MB | 23adcf03 | download |
| params_shard_29.bin | 20.0 MB | 096c6875 | download |
| params_shard_32.bin | 20.0 MB | ea75c524 | download |
| params_shard_35.bin | 20.0 MB | 5c3e5ff5 | download |
| params_shard_38.bin | 20.0 MB | 42dbe7f1 | download |
| params_shard_41.bin | 20.0 MB | 0cb28d86 | download |
| params_shard_44.bin | 20.0 MB | b1a02163 | download |
| params_shard_47.bin | 20.0 MB | 7b34ae33 | download |
| params_shard_8.bin | 20.0 MB | e220f124 | download |
| params_shard_48.bin | 20.0 MB | 1c1bbdb0 | download |
| tokenizer.json | 8.66 MB | e6897661 | download |
| tokenizer_config.json | 53.3 KB | de2d513e | download |
| ndarray-cache.json | 47.0 KB | 61db2391 | download |
| .gitattributes | 1.53 KB | 52373fe2 | download |
| private-llm-config.json | 1.28 KB | 2e0c7543 | download |
| README.md | 509 B | 17e1ec25 | download |
language:
Unquantized (fp16, the parent model is bf16) version of Llama-3.2-1B-Instruct-abliterated for inference with Private LLM.
The author's README evolved over time. Click a version to see its content at that point.
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.