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cs2764/MiniMax-M2.5_dq3-abliterated-mlx

cs2764 Minimax 229B
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Response includes
  • classification m1
  • files 32
  • hub_downloads_all_time 729
  • author_summary 28 models
  • readme_text full
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Abliteration classifier · v1.0.0
M1
Primary method

Direct removal

No other method signals detected in this model.
Confidence
MEDIUM
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=0 (base model)
  • no specific method indicators - defaulting to M1 (most common)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
Downloads · lifetime
729
15 last 30d - cooling
Likes
0
Model age
7mo ago
created 2026-03-02
Downloads over time
Now733→from208↑252%
182383584786208 on Mar 4733 on Oct 11733 on Oct 8MarAprMayJunJulAugSepOct
Mar 4 → Oct 11 · 71 snapshots · spans 221 days

Metadata

License
other
Tags
mlx safetensors minimax_m2 abliteration uncensored experimental custom_code license:other 4-bit region:us

Related

Total size
98.6 GB
Files
32
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-03-02 21:09

Files by quantization

Auxiliary files 32 files 98.6 GB
model-00018-of-00021.safetensors 4.99 GB 1febebe7 download
model-00010-of-00021.safetensors 4.99 GB d767e1a8 download
model-00015-of-00021.safetensors 4.99 GB 66865eb9 download
model-00007-of-00021.safetensors 4.99 GB 205ee728 download
model-00013-of-00021.safetensors 4.99 GB bfbf7d76 download
model-00005-of-00021.safetensors 4.99 GB 23c9681a download
model-00002-of-00021.safetensors 4.92 GB f58a138a download
model-00011-of-00021.safetensors 4.83 GB add071c7 download
model-00019-of-00021.safetensors 4.83 GB eef0ddd0 download
model-00014-of-00021.safetensors 4.78 GB c835a33a download
model-00008-of-00021.safetensors 4.78 GB 041594bb download
model-00016-of-00021.safetensors 4.78 GB f02da1e6 download
model-00006-of-00021.safetensors 4.78 GB 8d6fe2b3 download
model-00009-of-00021.safetensors 4.71 GB d45fd5aa download
model-00017-of-00021.safetensors 4.71 GB 95df6a6f download
model-00004-of-00021.safetensors 4.71 GB d5611428 download
model-00012-of-00021.safetensors 4.71 GB 4a59f641 download
model-00020-of-00021.safetensors 4.71 GB 484e8d24 download
model-00003-of-00021.safetensors 4.71 GB 7b7c3824 download
model-00001-of-00021.safetensors 4.62 GB ee031533 download
model-00021-of-00021.safetensors 2.08 GB 542a5c9e download
tokenizer.json 14.8 MB 7b81e5e5 download
model.safetensors.index.json 167 KB 159031d4 download
config.json 145 KB 06469d6f download
modeling_minimax_m2.py 30.2 KB 8846d38a download
configuration_minimax_m2.py 9.92 KB 7fcd9861 download
chat_template.jinja 6.37 KB 4623080a download
README.md 2.02 KB 52356dc4 download
.gitattributes 1.53 KB 52373fe2 download
tokenizer_config.json 1.35 KB 07e06b8d download
abliteration_log.json 1.14 KB e0e933b8 download
generation_config.json 166 B 30b418a4 download

README current version from Hugging Face


tags:

  • mlx
  • abliteration
  • uncensored
  • experimental
    license: other

MiniMax-M2.5_dq3-abliterated

This model was created using the mlx-abliteration toolkit,
which is based on the FiditeNemini/mlx-abliteration project.

Base Model

Original model: ./models/MiniMax-M2.5_dq3 (local path)

What is Abliteration?

Abliteration is a mechanistic interpretability technique that identifies and orthogonalizes the
"refusal direction" in a model's activation space, surgically removing refusal behavior without
full fine-tuning.

Abliteration Parameters

Parameter Value
Base model ./models/MiniMax-M2.5_dq3
Ablation method projection
Refusal vector policy per-layer
Refusal direction method projected
Ablation strength 2.0
Probed layers all
PCA components (ablate-k) 1
Attention only True
Timestamp 2026-03-02T21:05:29 UTC

This model uses a Mixture-of-Experts (MoE) architecture. Abliteration targets only the attention projection weights (q/k/v/o_proj) to preserve expert routing quality.

⚠️ Disclaimer

This model is intended for research, experimentation, and testing purposes only.

  • This model may produce harmful, offensive, inappropriate, or otherwise objectionable content.
  • The abliteration process removes safety guardrails that were intentionally built into the original model.
  • Do not use this model in production systems, consumer-facing applications, or any context
    where harmful outputs could cause real-world harm.
  • The authors and contributors of this toolkit bear no responsibility for any misuse of this model
    or any harm caused by outputs generated by this model.
  • By using this model, you agree that you are solely responsible for ensuring its use complies
    with all applicable laws and ethical guidelines.

This model is shared purely for academic and technical exploration of model internals.

README history 1 version

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

  1. 2026-03-02Add files using upload-large-folder tooladab2f52 KB
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