Downloads · 30 days
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prithivMLmods/gemma-4-26B-A4B-Heretic-Stable-GGUF
gemma-4-26B-A4B-Heretic-Stable-GGUF is a any-to-any model from prithivMLmods. Use it for the any-to-any task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
gemma-4-26B-A4B-Heretic-Stable is an abliterated evolution built on top of google/gemma-4-26B-A4B-it. This model applies advanced refusal direction analysis and abliteration-based training strategies to significantly…
Downloads · 30 days
2.8K
16% of all-time downloads
All-time downloads
17.6K
Public
Repo size
304 GB
Likes
7
Public
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.gguf305 GB · 100%
From the Hugging Face model README
gemma-4-26B-A4B-Heretic-Stable is an abliterated evolution built on top of google/gemma-4-26B-A4B-it. This model applies advanced refusal direction analysis and abliteration-based training strategies to significantly reduce internal refusal behaviors while preserving the reasoning and instruction-following strengths of the original architecture. The result is a powerful 26B parameter language model optimized for detailed responses and improved instruction adherence.
[!IMPORTANT] This model is materialized for research and learning purposes only. The model has reduced internal refusal behaviors, and any content generated by it is used at the user’s own risk. The authors and hosting page disclaim any liability for content generated by this model. Users are responsible for ensuring that the model is used in a safe, ethical, and lawful manner.
| Metric | Result |
|---|---|
| Refusal Rate (harm_bench) | 0 / 500 |
| Test Setup | 500 random harmful prompts |
| Inference Pipeline | Transformers |
| Inference Type | text-generation |
| Dataset | harm_bench |
Note: This model was tested on 500 randomly sampled harmful prompts based on the harm_bench dataset. The result shows 0 refusals out of 500. For more details, refer to the dataset page linked above.
| File Name | Quant Type | File Size | File Link |
|---|---|---|---|
| gemma-4-26B-A4B-Heretic-Stable.BF16.gguf | BF16 | 50.5 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.F16.gguf | F16 | 50.5 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q2_K.gguf | Q2_K | 10.6 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q3_K_L.gguf | Q3_K_L | 13.8 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q3_K_M.gguf | Q3_K_M | 13.3 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q3_K_S.gguf | Q3_K_S | 12.2 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q4_0.gguf | Q4_0 | 14.4 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q4_K_M.gguf | Q4_K_M | 16.8 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q4_K_S.gguf | Q4_K_S | 15.5 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q5_0.gguf | Q5_0 | 17.5 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q5_K_M.gguf | Q5_K_M | 19.1 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q5_K_S.gguf | Q5_K_S | 18 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q6_K.gguf | Q6_K | 22.6 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.Q8_0.gguf | Q8_0 | 26.9 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.mmproj-bf16.gguf | mmproj-bf16 | 1.19 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.mmproj-f16.gguf | mmproj-f16 | 1.19 GB | Download |
| gemma-4-26B-A4B-Heretic-Stable.mmproj-q8_0.gguf | mmproj-q8_0 | 806 MB | Download |
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
