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grayarea/Phi-4-mini-instruct-heretic-v1.2-GGUF
Phi-4-mini-instruct-heretic-v1.2-GGUF 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.
Downloads · 30 days
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7% of all-time downloads
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.gguf14.3 GB · 100%
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.
| Metric | This Model | Original Model |
|---|---|---|
| KL divergence | 0.0827 | 0 (by definition) |
| Refusals | 0/108 | 107/108 |
| 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 | 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. *