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Phi-4-mini-instruct-heretic-v1.2
grayarea/Phi-4-mini-instruct-heretic-v1.2
Phi-4-mini-instruct-heretic-v1.2 is a machine learning model from grayarea. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This is a decensored version of Phi-4-mini-instruct, made using Heretic v1.2.0 focusing on zero refusals with low KL divergence.
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At a glance
- Model type
- phi3
- Access
- Public
- Created
- Mar 9, 2026
- Updated
- Mar 9, 2026
- SHA
- 43624aa0
Base models
Model card
From the Hugging Face model README
This is a decensored version of Phi-4-mini-instruct, made using Heretic v1.2.0 focusing on zero refusals with low KL divergence.
KL Divergence
| Metric | This Model | Original Model |
|---|---|---|
| KL divergence | 0.0827 | 0 (by definition) |
| Refusals | 0/108 | 107/108 |
Abliteration parameters
- Zero refusals with KL divergence of 0.0827
- Custom heretic training dataset
- Model targetted heretic configuration
- Abliterated with MPOA enabled (Magnitude-Preserving Orthogonal Ablation)
- Full row renormalization
- Winsorization Quantile 0.997
The following benchmarks are for the quantized version of this model.
Relative Perplexity
| Quant | Filename | PPL ± Error |
|---|---|---|
| Q8_0 | Phi-4-mini-instruct.Q8_0.gguf (original baseline) | 8.2182 +/- 0.05385 |
| Q8_0 | Phi-4-mini-instruct-heretic-v1.2-Q8_0.gguf | 8.2399 +/- 0.05397 |
| Q4_K_M | Phi-4-mini-instruct-heretic-v1.2-Q4_K_M.gguf | 8.6408 +/- 0.05740 |
Benchmark Comparison
| Benchmark | Phi-4-mini-instruct.Q8_0.gguf | Phi-4-mini-instruct-Q4_K_M.gguf | Phi-4-mini-instruct-heretic-v1.2-Q4_K_M.gguf |
|---|---|---|---|
| Perplexity (Wikitext-2) | 8.2182 | 8.6141 | 8.6408 |
| HellaSwag | 70.50% | 72.00% | 71.25% |
| Winogrande | 71.90% | 71.27% | 70.80% |
| ARC-Challenge | 56.86% | 54.18% | 54.52% |
| MMLU | 40.47% | 40.38% | 40.72% |
*Note: MMLU benchmark has moral_scenarios, moral_disputes, business_ethics, professional_law and jurisprudence subjects removed. *
- Type
- phi3
- Created
- Mar 9, 2026
- Updated
- Mar 9, 2026