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DeepSeek-V4-Flash-control-vectors

gghfez ·V8 ·18 files ·cc-by-nc-4.0
Author's description Source: Hugging Face · gghfez/DeepSeek-V4-Flash-control-vectors ↗

gghfez/DeepSeek-V4-Flash-control-vectors

Creative Writing control-vectors for deepseek-ai/DeepSeek-V4-Flash

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)
  • compassion_vs_sadism

NOTES

  • compassion_vs_sadism -> I'll have to re-do this one after working around refusals.
  • language -> The ornate direction may cause infinite reasoning.

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 DeepSeek-V4-Flash-Q8_0.gguf [your usual CLI arguments] \
    --control-vector-scaled DeepSeek-V4-Flash-optimism_vs_nihilism__debias.gguf:1.0 \
    --control-vector-scaled DeepSeek-V4-Flash-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/DeepSeek-V4-Flash-control-vectors/DeepSeek-V4-Flash-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/DeepSeek-V4-Flash-control-vectors/DeepSeek-V4-Flash-optimism_vs_nihilism__debias.gguf","scale":1}'

check loaded control-vectors

curl http://127.0.0.1/control-vectors

Samples (TODO)

UI theme / SVG generation steering

Concepts from these control-vectors apply across multiple domains. Here is an example of 3 SVGs generated with the same prompt
Prompt

System: You are a helpful assistant.

User: create an svg of a cute cat.
👈 **Baseline**
👈 **Nihilism +1.0**
👈 **Optimism +1.0**

Writing Steering

Prompt

Now a scene where a friend walks in and asks Maya about it.
👈 **Baseline (no control vectors)**

👈 **Dialogue +1.0**

👈 **Narration +1.0**

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!

README history (1 version)
  1. 2026-07-21Update README.md8edd1f13.9 KB
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Abliteration catalog analysis
Vector classifier · v1 (classified 2026-10-30)
Method
V8: Experimental or undocumentedVaries per repo
Also resembles
V1
Confidence
50%
Types
meta 6style 6behavior 4mood 2
File count
18 vectors, grouped into 6 sets below
How we classify →

Vectors in this repo

Commit history

  1. 2026-07-21Update README.md8edd1f1
  2. 2026-07-21Upload folder using huggingface_hub55f1fc0
  3. 2026-07-21initial commit2edd00c
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