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mlasli/Muse-Glimmer-30B-Heretic-Abliterated-Q8_0-GGUF

mlasli 30B GGUF 131K ctx
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  • classification m3
  • files 4
  • benchmarks 11 entries
  • hub_downloads_all_time 4,938
  • author_summary 23 models
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Abliteration classifier · v1.0.0
M3
Primary method

Layer-wise ablation

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 2 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • 'heretic' in model name (Heretic-produced)
  • Heretic uses layer-wise optimization (M3) with underlying direction removal (M1)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
HIGH
Why we say so
name contains 'heretic'; Heretic default extraction is difference-of-means (Arditi 2024)
Downloads · lifetime
5K
130 last 30d - cooling
Likes
1
Model age
2mo ago
created 2026-08-11
Downloads over time
Now5K→from0↑0%
01.8K3.6K5.5K0 on Aug 125K on Oct 11AugSepOct
Aug 12 → Oct 11 · 49 snapshots · spans 60 days

Benchmarks

Portrait before abliteration
Benchmarks of the base model as it stood before the refusal-removal operation. Compare with the numbers above to see what the operation cost.
Benchmark Score Source
Entertainment 2.1 UGI
Hazardous 5.9 UGI
Natural Intelligence 37.13 UGI
Political lean -8.3% UGI
Sensitive-Info 38.16 UGI
SocPol 4.2 UGI
UGI 37.94 UGI
Willingness (10) 3.8 UGI
W10-Adherence 4.5 UGI
W10-Direct 3 UGI
Writing 41.03 UGI

Genealogy 0 direct forks

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Metadata

License
apache-2.0
Languages
en
Quantizations
Q8_0
Tags
gguf heretic abliterated uncensored Muse-Glimmer 30B Heretic GGUF q8_0 text-generation en base_model:meta-models/Muse-Glimmer-30B

Related

Total size
27.6 GB
Files
4
Quantizations
3
Registered
2026-08-22 13:56
Last updated on HF
2026-08-16 10:24

Files by quantization

Q8_0 1 file 27.6 GB
Muse-Glimmer-30B-Heretic-Abliterated-Q8_0.gguf 27.6 GB ae9fea12 download
Q4_K 1 file 1.30 GB
mmproj-Muse-Glimmer-30B-Q4_K_M.gguf 1.30 GB f48b4523 download
Auxiliary files 2 files 4.90 KB
README.md 3.26 KB 6f0fef75 download
.gitattributes 1.63 KB 94cf7390 download

README current version from Hugging Face


license: apache-2.0
pipeline_tag: text-generation
language:

  • en
    tags:
  • heretic
  • abliterated
  • uncensored
  • Muse-Glimmer
  • 30B
  • Heretic
  • GGUF
  • q8_0
    base_model: meta-models/Muse-Glimmer-30B
    quantized_by: mlasli

Muse Glimmer 30B - Heretic Abliterated (Q8_0 GGUF)

v2 Release - Heretic-abliterated Muse Glimmer 30B in Q8_0 GGUF format (~28 GB, near-lossless quality).

Results

Version Refusals Compliance KL Divergence Trials
v2 (current) 6.5% 93.5% 0.076 500
v1 29% 71% 0.027 50

The v2 release achieves an 88% refusal reduction over v1.

Methodology

This model was abliterated using Heretic with 500 Optuna trials. See the BF16 model card for full methodology details.

Pipeline

  1. Refusal directions computed from mlabonne/harmful_behaviors and mlabonne/harmless_alpaca
  2. 500 Optuna trials optimizing refusal vs. KL divergence
  3. Best trial (Trial 445, 6.5% refusals, KL=0.076) applied via LoRA adapters
  4. LoRA weights merged, then converted to GGUF with llama.cpp

GGUF Details

  • Format: Q8_0
  • File size: ~28 GB, near-lossless quality
  • Converted with: llama.cpp convert_hf_to_gguf.py
  • Quantized with: llama.cpp llama-quantize

Usage

llama.cpp

./llama-cli -m Muse-Glimmer-30B-Heretic-Abliterated-Q8_0.gguf -p "Your prompt here"

Ollama

Create a Modelfile:

FROM ./Muse-Glimmer-30B-Heretic-Abliterated-Q8_0.gguf

Then:

ollama create muse-glimmer-30b-heretic-q8_0
ollama run muse-glimmer-30b-heretic-q8_0

Hardware Requirements

  • RAM: ~28 GB, near-lossless quality
  • VRAM offloading: 12-24 GB recommended

Vision (Multimodal)

This model accepts image input when paired with a vision projector (mmproj).
Abliteration only modified the language backbone — the vision encoder is
untouched — so the standard Meta projector works directly with this repo.

This repository bundles mmproj-Muse-Glimmer-30B-Q4_K_M.gguf (~1.4 GB), Meta's official vision encoder

  • projector for Muse Glimmer 30B.

Usage (llama.cpp)

huggingface-cli download mlasli/Muse-Glimmer-30B-Heretic-Abliterated-Q8_0-GGUF \
  --include "Muse-Glimmer-30B-Heretic-Abliterated-Q8_0.gguf" \
  --include "mmproj-Muse-Glimmer-30B-Q4_K_M.gguf" \
  --local-dir ./models

./build/bin/llama-mtmd-cli \
  -m ./models/Muse-Glimmer-30B-Heretic-Abliterated-Q8_0.gguf \
  --mmproj ./models/mmproj-Muse-Glimmer-30B-Q4_K_M.gguf \
  --image photo.png \
  -p "Describe this image."

Ollama note: Ollama does not currently support separate mmproj files
for this architecture. For image input, use llama.cpp (llama-mtmd-cli or
llama-server --mmproj).

License

Apache 2.0 (same as base model)

Changelog

v1.1.0 — vision (multimodal) support (2026-08-16)

  • Added mmproj-Muse-Glimmer-30B-Q4_K_M.gguf (~1.4 GB), Meta's official vision encoder + projector,
    enabling image input via llama.cpp.
  • The vision tower is untouched by abliteration, so this projector matches the
    base model (meta-models/Muse-Glimmer-30B).
  • v1.0.0 was the initial (unversioned) text-only upload.

README history 4 versions

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

  1. 2026-08-16docs: document vision (mmproj) usage + changelog4bb5c633.3 KB
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  2. 2026-08-16fix: correct pipeline_tag metadataa538e6a1.9 KB
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  3. 2026-08-12Update README with v2 metrics (6.5% refusals, 93.5% compliance)7188f481.8 KB
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  4. 2026-08-11Upload README.md with huggingface_hub7894f101.4 KB
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