You can deploy this model and start earning money today!

YanLabs/
Seed-OSS-36B-Instruct-MPOA-v1-GGUF

Name: Seed-OSS-36B-Instruct-MPOA-v1-GGUF
Availability: InStock

gguf

text-generation

YanLabs/Seed-OSS-36B-Instruct-MPOA-v1

quantized

apache-2.0

endpoints_compatible

Views

No views yet

YanLabs/Seed-OSS-36B-Instruct-MPOA-v1

This model is a variant of YanLabs/Seed-OSS-36B-Instruct-MPOA. The current model is less abliterated to preserve the capability of original model. Refusals might occur at quants lower than F16, but I like its style of writing when it does not refuse.

This is an abliterated version of ByteDance-Seed/Seed-OSS-36B-Instruct using the norm-preserving biprojected abliteration technique.

⚠️ Warning: Safety guardrails and refusal mechanisms have been removed through abliteration. This model may generate harmful content and is intended for mechanistic interpretability research only.

Model Details

Model Description

This model applies norm-preserving biprojected abliteration to remove refusal behaviors while preserving the model's original capabilities. The technique surgically removes "refusal directions" from the model's activation space without traditional fine-tuning.

Developed by: YanLabs
Model type: Causal Language Model (Transformer)
License: apache-2.0
Base model: ByteDance-Seed/Seed-OSS-36B-Instruct

Model Sources

Base Model: ByteDance-Seed/Seed-OSS-36B-Instruct
Abliteration Tool: jim-plus/llm-abliteration
Paper: Norm-Preserving Biprojected Abliteration

Uses

Intended Use

Research: Mechanistic interpretability studies
Analysis: Understanding LLM safety mechanisms
Development: Testing abliteration techniques

Out-of-Scope Use

❌ Production deployments
❌ User-facing applications
❌ Generating harmful content for malicious purposes

Limitations

Abliteration does not guarantee complete removal of all refusals
May generate unsafe or harmful content
Model behavior may be unpredictable in edge cases
No explicit harm prevention mechanisms remain

Citation

If you use this model in your research, please cite:

bibtex

@misc{Seed-OSS-36B-Instruct-MPOA,
  author = {YanLabs},
  title = {Seed-OSS-36B-Instruct-MPOA},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/YanLabs/Seed-OSS-36B-Instruct-MPOA}},
  note = {Abliterated using norm-preserving biprojected technique}
}

YanLabs/Seed-OSS-36B-Instruct-MPOA-v1-GGUF

YanLabs/Seed-OSS-36B-Instruct-MPOA-v1

Model Details

Model Description

Model Sources

Uses

Intended Use

Out-of-Scope Use

Limitations

Citation

YanLabs/
Seed-OSS-36B-Instruct-MPOA-v1-GGUF