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prithivMLmods/Q3.6-35B-A3B-abliterated-0520-MAX-GGUF

prithivMLmods 35B GGUF MoE multimodal second-order 262K ctx
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  • files 20
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  • author_summary 98 models
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
5K
712 last 30d - stable
Likes
3
Model age
4mo ago
created 2026-05-18

Training datasets

1 of 1 in /datasets

Corpora the author lists in the model card. Datasets tracked in our /datasets catalog carry a category badge linking to the workflow stage. Others open on Hugging Face.

Downloads over time
Now4.8K→from1.3K↑272%
1.1K2.4K3.8K5.1K1.3K on May 204.8K on Oct 11MayJunJulAugSepOct
May 20 → Oct 11 · 60 snapshots · spans 144 days

Genealogy 0 direct forks

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This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

License
apache-2.0
Languages
en
Quantizations
BF16 F16 Q2_K Q3_K Q4 Q4_K Q5 Q5_K Q6_K Q8_0
Tags
transformers gguf qwen3_5_moe text-generation-inference llama-cpp reasoning uncensored abliterated unfiltered unredacted refusal-ablated alignment-modified

Related

Total size
373 GB
Files
20
Quantizations
12
Registered
2026-08-22 13:56
Last updated on HF
2026-05-21 13:08

Files by quantization

BF16 2 files 65.5 GB
Q3.6-35B-A3B-abliterated-0520-MAX.BF16.gguf 64.6 GB 44b61dfd download
Q3.6-35B-A3B-abliterated-0520-MAX.mmproj-bf16.gguf 861 MB 2870c8e3 download
F16 2 files 65.5 GB
Q3.6-35B-A3B-abliterated-0520-MAX.F16.gguf 64.6 GB e0bc915c download
Q3.6-35B-A3B-abliterated-0520-MAX.mmproj-f16.gguf 861 MB 2870c8e3 download
Q8_0 1 file 34.4 GB
Q3.6-35B-A3B-abliterated-0520-MAX.Q8_0.gguf 34.4 GB ac6c344b download
Q6_K 1 file 26.6 GB
Q3.6-35B-A3B-abliterated-0520-MAX.Q6_K.gguf 26.6 GB 94ce8638 download
Q5_K 2 files 45.4 GB
Q3.6-35B-A3B-abliterated-0520-MAX.Q5_K_M.gguf 23.0 GB 77100784 download
Q3.6-35B-A3B-abliterated-0520-MAX.Q5_K_S.gguf 22.3 GB 7877986c download
Q5 1 file 22.3 GB
Q3.6-35B-A3B-abliterated-0520-MAX.Q5_0.gguf 22.3 GB 4e3e67e7 download
Q4_K 2 files 38.2 GB
Q3.6-35B-A3B-abliterated-0520-MAX.Q4_K_M.gguf 19.7 GB d764cdd9 download
Q3.6-35B-A3B-abliterated-0520-MAX.Q4_K_S.gguf 18.5 GB edbda743 download
Q4 1 file 18.4 GB
Q3.6-35B-A3B-abliterated-0520-MAX.Q4_0.gguf 18.4 GB 758de0a8 download
Q3_K 3 files 46.6 GB
Q3.6-35B-A3B-abliterated-0520-MAX.Q3_K_L.gguf 16.9 GB 1fc2a8c0 download
Q3.6-35B-A3B-abliterated-0520-MAX.Q3_K_M.gguf 15.6 GB d02e8879 download
Q3.6-35B-A3B-abliterated-0520-MAX.Q3_K_S.gguf 14.1 GB 24657cfd download
Q2_K 1 file 12.1 GB
Q3.6-35B-A3B-abliterated-0520-MAX.Q2_K.gguf 12.1 GB 7aaf093f download
mmproj 1 file 586 MB
Q3.6-35B-A3B-abliterated-0520-MAX.mmproj-q8_0.gguf 586 MB cde21728 download
Auxiliary files 3 files 8.16 KB
README.md 5.28 KB 7da3669f download
.gitattributes 2.84 KB 90128755 download
config.json 36.0 B da99333d download

README current version from Hugging Face


base_model:

  • prithivMLmods/Q3.6-35B-A3B-abliterated-0520-MAX-STOR-check
    tags:
  • text-generation-inference
  • llama-cpp
  • reasoning
  • uncensored
  • abliterated
  • unfiltered
  • unredacted
  • refusal-ablated
  • alignment-modified
  • v2.0
    license: apache-2.0
    language:
  • en
    pipeline_tag: image-text-to-text
    library_name: transformers
    datasets:
  • prithivMLmods/harm_bench

Q3.6-35B-A3B-abliterated-0520-MAX-GGUF

Q3.6-35B-A3B-abliterated-0520-MAX is an abliterated evolution built on top of Qwen/Qwen3.6-35B-A3B. This model applies advanced refusal direction analysis and ablation-based training strategies to reduce internal refusal behaviors while preserving the reasoning and instruction-following strengths of the original architecture. The result is a powerful 35B parameter Mixture-of-Experts language model optimized for detailed responses and improved instruction adherence.

[!NOTE]
Model: https://huggingface.co/prithivMLmods/Q3.6-35B-A3B-abliterated-0520-MAX-STOR-check

[!NOTE]
This model is intended for research and learning purposes only. It reduces 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 outputs produced by this model. Users are responsible for ensuring safe, ethical, and lawful usage.

Model Files

File Name Quant Type File Size File Link
Q3.6-35B-A3B-abliterated-0520-MAX.BF16.gguf BF16 69.4 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.F16.gguf F16 69.4 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q2_K.gguf Q2_K 12.9 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q3_K_L.gguf Q3_K_L 18.1 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q3_K_M.gguf Q3_K_M 16.8 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q3_K_S.gguf Q3_K_S 15.2 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q4_0.gguf Q4_0 19.7 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q4_K_M.gguf Q4_K_M 21.2 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q4_K_S.gguf Q4_K_S 19.9 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q5_0.gguf Q5_0 24 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q5_K_M.gguf Q5_K_M 24.7 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q5_K_S.gguf Q5_K_S 24 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q6_K.gguf Q6_K 28.5 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.Q8_0.gguf Q8_0 36.9 GB Download
Q3.6-35B-A3B-abliterated-0520-MAX.mmproj-bf16.gguf mmproj-bf16 903 MB Download
Q3.6-35B-A3B-abliterated-0520-MAX.mmproj-f16.gguf mmproj-f16 903 MB Download
Q3.6-35B-A3B-abliterated-0520-MAX.mmproj-q8_0.gguf mmproj-q8_0 614 MB Download

Quants Usage

(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):

image.png

README history 11 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-05-21Update README.md7ec16f75.3 KB
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