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Reading real hardware from your app right now. Numbers below are exact.
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-w4a16g128asym" 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 | 125 MB | efc6b792 | download |
| params_shard_2.bin | 32.0 MB | 2d446f85 | download |
| params_shard_1.bin | 31.8 MB | 72972ef9 | download |
| params_shard_10.bin | 29.9 MB | 4a9a9025 | download |
| params_shard_11.bin | 29.9 MB | 57ee192a | download |
| params_shard_12.bin | 29.9 MB | 8d9c13fb | download |
| params_shard_13.bin | 29.9 MB | 2333440a | download |
| params_shard_14.bin | 29.9 MB | 48496e46 | download |
| params_shard_15.bin | 29.9 MB | 10ab869f | download |
| params_shard_16.bin | 29.9 MB | 074750b6 | download |
| params_shard_3.bin | 29.9 MB | f5bf9f98 | download |
| params_shard_4.bin | 29.9 MB | 99340066 | download |
| params_shard_5.bin | 29.9 MB | 71ec8adb | download |
| params_shard_6.bin | 29.9 MB | 77001614 | download |
| params_shard_7.bin | 29.9 MB | afd9b5c4 | download |
| params_shard_8.bin | 29.9 MB | 1c7e2d22 | download |
| params_shard_9.bin | 29.9 MB | 3c4fba8b | download |
| tokenizer.json | 8.66 MB | 777c28bc | download |
| ndarray-cache.json | 64.4 KB | 52d4a931 | download |
| tokenizer_config.json | 53.4 KB | 9325164d | download |
| .gitattributes | 1.48 KB | a6344aac | download |
| private-llm-config.json | 1.29 KB | 17b60f5b | download |
| README.md | 447 B | 11c2d4b5 | download |
| config.json | 55.0 B | d9e7e08f | download |
language:
4-bit OmniQuant quantized version of Llama-3.2-1B-Instruct-abliterated.
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.