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MiniMax-M3-control-vectors

gghfez ·V1 ·21 files ·cc-by-nc-4.0
Author's description Source: Hugging Face · gghfez/MiniMax-M3-control-vectors ↗

gghfez/MiniMax-M3-control-vectors

TODO

Creative Writing control-vectors for MiniMaxAI/MiniMax-M3

What are Control Vectors?

Control vectors steer model behavior without retraining by adjusting
activations in specific directions.

These creative writing vectors help
you tune narrative tone, character focus, and stylistic elements.

Available Vectors

  • optimism_vs_nihilism
  • empathy_vs_sociopathy
  • honesty_vs_machiavellianism
  • humility_vs_narcissism
  • character focus (dialogue_vs_narration)
  • language (simple vs ornate)
  • storytelling (descriptive vs explicit)

Usage

Apply the debias vector and either the positive or negative vector when starting llama-server.
If both axes are applied at the same time, they will cancel each other out.
The debias vector must be set to 1.0

You can use either --control-vector [/path/to/vector.gguf] or --control-vector-scaled [/path/to/vector.gguf] [scale factor]

When using ik_llama.cpp, you can also use the REST-API (examples below)

IMPORTANT: As these vectors are calibrated against the debiased model, the debias vector must be applied along with the corresponding positive or negative axis control vector - they cannot be used on their own!

Examples (ik_llama.cpp or llama.cpp)

At server start-up

llama-server --model MiniMax-M3-Q8_0.gguf [your usual CLI arguments] \
    --control-vector-scaled MiniMax-M3-optimism_vs_nihilism__debias.gguf 1.0 \
    --control-vector-scaled MiniMax-M3-optimism_vs_nihilism__nihilism.gguf 1.0 \

At server start-up with thinking disabled

llama-server --model MiniMax-M3-Q8_0.gguf [your usual CLI arguments] \
    --chat-template-kwargs '{"enable_thinking": false}' \
    --control-vector-scaled MiniMax-M3-optimism_vs_nihilism__debias.gguf 1.0 \
    --control-vector-scaled MiniMax-M3-optimism_vs_nihilism__nihilism.gguf 1.0 \

Load via API (ik_llama.cpp only)

load direction vector

curl 'http://127.0.0.1:8080/control-vectors/load' \
  -X POST \
  --data-raw '{"path":"/path/to/MiniMax-M3-control-vectors/MiniMax-M3-optimism_vs_nihilism__nihilism.gguf","scale":1}'

load debias vector

 curl 'http://127.0.0.1:8080/control-vectors/load' \
  -X POST \
  --data-raw '{"path":"/path/to/MiniMax-M3-control-vectors/MiniMax-M3-optimism_vs_nihilism__debias.gguf","scale":1}'

check loaded control-vectors

curl http://127.0.0.1/control-vectors

Samples

TODO

Acknowledgements

Based on the excellent work and cross-covariance eigendecomposition implementation by @jukofyork. His creative writing control vectors v3.0 repository contains the foundational code and methodology that made this possible, plus 70+ other creative writing control vectors across many models and useful steering directions.
Highly recommended for anyone working on improving LLM prose quality!

Abliteration catalog analysis
Vector classifier · v1 (classified 2026-10-30)
Method
V1: PCA on contrastive pairsZou et al. 2023, Representation Engineering; Vogel 2024, repeng
Also resembles
V8
Confidence
70%
Types
meta 7style 6behavior 6mood 2
File count
21 vectors, grouped into 7 sets below
How we classify →

Vectors in this repo

Commit history

  1. 2026-09-05Upload folder using huggingface_hubc1a4a0c
  2. 2026-09-05initial commit143ff9f
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