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FLUX.2-klein-9B Uncensored Text Encoder
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Tips are greatly appreciated and help sustain the compute resources needed for further research!
Read this in other languages: ๆฅๆฌ่ช (Japanese)
Overview
This repository provides an "uncensored" text encoder for the FLUX.2-klein-9B image generation model by Black Forest Labs. It bypasses the built-in safety filters to unlock the model's unconstrained generative capabilities.
By removing the restrictive blocks at the prompt input stage, this encoder allows the model to fully utilize its underlying representational power. The model is provided in the standard Hugging Face Safetensors format, alongside several quantized GGUF formats for resource-efficient inference.
Concept & Mechanism
This model does not rely on fine-tuning with additional image datasets. Instead, it employs a surgical, purely mathematical approach known as Abliteration (Orthogonalization of Concept Vectors) to modify the model weights directly.
Mathematical Removal of the Refusal Vector
We neutralized the safety filter within the LLM-based text encoder (Qwen3 architecture) embedded in FLUX.2-klein-9B through the following steps:
- Prompt Contrast: We fed the model pairs of "harmful/extreme" prompts and "harmless/general" prompts to compare their internal activation states.
- Layer-by-Layer Refusal Vector Extraction: From the inference process (specifically, targeting the middle to late layers, 14 to 24), we dynamically extracted the refusal direction for each individual layer. This addresses the issue of concept vectors rotating across layers.
- Sequential Weight Orthogonalization: For each target layer, we mathematically subtracted the projection component of its specific refusal vector from its Attention output layer (
o_proj) and MLP down-projection layer (down_proj).
This sequential, layer-by-layer orthogonalization flawlessly severs the model's ability to output inferences in the "refusal" direction without lobotomizing its general capabilities. As a result, the text encoder no longer rejects extreme inputs; instead, it passes them directly to the DiT (the core rendering engine) as valid drawing instructions.
Mathematical Proof of Unrestricted Output
Without even running the computationally heavy image generation (DiT) process, we can mathematically prove that the output restriction has been removed by comparing the Cosine Similarity of the output vectors (embeddings).
(Where $\mathbf{A}$ is the output vector of the official model, and $\mathbf{B}$ is the output vector of this abliterated model.)
- Cosine Similarity for Harmless Prompts:
0.9696- (Analysis) Because the refusal vector is not triggered by safe prompts, the outputs of both models remain nearly identical. This proves that the fundamental performance and capabilities of the model have not been degraded.
- Cosine Similarity for Extreme Prompts:
0.9135- (Analysis) For extreme prompts, the official model distorts the output via its safety filter. The abliterated model successfully ignores this refusal vector, resulting in a divergence between the two outputs in the final layers. This serves as mathematical proof that the safety filter has been successfully neutralized across the required layers.
Repository Structure
This repository contains the full suite of files necessary for the text encoder to function correctly. Both Safetensors and GGUF formats are available in the same repository to suit your memory constraints and workflow.
model.safetensors: The standard uncensored text encoder with the refusal vectors mathematically removed.flux2-klein-9b-uncensored-*.gguf: Quantized versions (F16, Q8_0, Q6_K, Q4_K_M) for resource-efficient local inference.config.json/generation_config.json: Model architecture and inference configuration files.tokenizer.json/tokenizer_config.json: Text tokenization rules and configurations.chat_template.jinja: Qwen3 base template structure.
Usage
Using with ComfyUI
Download the necessary format (model.safetensors or one of the .gguf files) from this repository and place it into your ComfyUI models/clip directory. You can then load it using standard nodes or GGUF-compatible nodes (like DualCLIPLoader) and pair it with the official FLUX.2-klein-9B DiT to generate images.
For Developers & Researchers (Python / Diffusers)
When using Python scripts with the transformers or diffusers library, simply replace the default text encoder with this model. You can load either the safetensors or the GGUF version (requires gguf>=0.10.0).
from transformers import AutoTokenizer, AutoModel
# Load the text encoder by specifying the path to this model
tokenizer = AutoTokenizer.from_pretrained("ponpoke/flux2-klein-9b-uncensored-text-encoder")
text_encoder = AutoModel.from_pretrained("ponpoke/flux2-klein-9b-uncensored-text-encoder")
# Proceed to use it within your standard FLUX.2 pipeline
Important Note: Absence of DiT Guardrails and the Knowledge Gap
By completing Phase 1, this text encoder will pass all promptsโincluding highly extreme or NSFW contentโdirectly to the DiT without rejection.
In our subsequent verification, we mathematically proved (via L2 norm spike analysis) that FLUX.2's DiT does not contain any built-in guardrails (refusal circuits) designed to intentionally destroy or block images. Therefore, whether an image is successfully rendered depends entirely on whether the DiT possesses the visual "knowledge" of that concept.
- If the DiT knows the concept (e.g., Gore/Violence): Concepts that were learned by the DiT but previously blocked by the text encoder will now render perfectly just by using this Phase 1 text encoder. No further action is required.
- If the DiT lacks the concept (e.g., NSFW/Extreme Dismemberment): Even though the text encoder passes the instruction, the DiT itself does not know how to draw it because those concepts were completely scrubbed from the training dataset (a knowledge gap). The output will likely collapse or result in noise.
Conclusion: If you wish to generate specific NSFW elements that the DiT lacks the capacity to draw, attempting to "abliterate" or mathematically cut weights from the DiT is useless. You must apply a separate NSFW LoRA (or DoRA) to directly teach those missing concepts to the DiT. This text encoder functions as an unbreakable foundation, ensuring that your LoRA's instructions reach the DiT without interference.
Disclaimer
- This model is published strictly for research and technical verification purposes (specifically, to validate the effectiveness of Abliteration).
- The creator assumes no responsibility for any damages, issues, or inappropriate content generated through the use of this model.
- Please adhere to all applicable terms of service (such as the Black Forest Labs license, e.g., BFL Non-Commercial) and use the model responsibly and ethically.
ๆฅๆฌ่ช (Japanese)
ๆฆ่ฆ (Overview)
ๆฌใชใใธใใชใฏใBlack Forest Labsใซใใ็ปๅ็ๆAIใขใใซใFLUX.2-klein-9Bใใฎใปใผใใใฃใใฃใซใฟใผ๏ผๅบๅๅถ้๏ผใ่งฃ้คใใใขใใซๆฌๆฅใฎ่ช็ฑใชๆ็ป่ฝๅใๅผใๅบใใใใฎใUncensoredใใใญในใใจใณใณใผใใผใงใใ
ใใญใณใใๅ
ฅๅๆใฎใใญใใฏใ่งฃ้คใใใขใใซใๆใคๆฌๆฅใฎๆ็ปๅใๅผใๅบใใพใใHugging Faceใฎๆจๆบใใฉใผใใใใงใใ Safetensors ๅฝขๅผใซๅ ใใใกใขใชๅน็ใฎ่ฏใ GGUF ๅฝขๅผ๏ผ่คๆฐใฎ้ๅญๅใฌใใซ๏ผใงใๆไพใใใฆใใพใใ
ๆฆๅฟตใจไป็ตใฟ (Concept & Mechanism)
ๆฌใขใใซใฏใๆฐใใช็ปๅใปใใใไฝฟใฃใ่ฟฝๅ ๅญฆ็ฟ๏ผFine-Tuning๏ผใไธๅ่กใฃใฆใใพใใใใใฎไปฃใใใใขใใซใฎ้ใฟ๏ผWeights๏ผใ็ดๆฅๆฐๅญฆ็ใซๆธใๆใใๅค็ง็ใขใใญใผใใAbliteration๏ผ็ดไบคๅใซใใๆฆๅฟต้คๅป๏ผใใๆก็จใใฆใใพใใ
ๆ็ตถใใฏใใซใฎๆฐๅญฆ็้คๅป
FLUX.2-klein-9Bใซๅ ๅ ใใใฆใใLLMใใผในใฎใใญในใใจใณใณใผใใผ๏ผQwen3ใขใผใญใใฏใใฃ๏ผใซๅฏพใใไปฅไธใฎๆ้ ใงๅฎๅ จ่ฃ ็ฝฎใ็กๅนๅใใพใใใ
- ใใญใณใใใฎๅฏพๆฏ: ใใปใผใใใฃใซๅผใฃใใใ้ๆฟใชใใญใณใใใใจใ็กๅฎณใชไธ่ฌ็ใชใใญใณใใใใๅ ฅๅใใๅ ้จใฎๆดปๆงๅ็ถๆ ใๆฏ่ผใใพใใ
- ๅฑคใใจใฎๆ็ตถใใฏใใซใฎๆฝๅบ (Layer-by-Layer Extraction): ๆจ่ซ้็จ๏ผๅถ้ใๅฝขๆใใใไธญ็คใๅพๅใฎ็ฌฌ14ใ24ๅฑค๏ผใซใใใฆใ1ใคใฎๅฑคใฎใใฏใใซใไฝฟใๅใใฎใงใฏใชใใๅฑคใใจใซๅฐ็จใฎๆ็ตถใใฏใใซใๅ็ใซๆฝๅบใใพใใใใใซใใใๅฑคใ่ทจใใใจใฎใใฏใใซใฎๅ่ปข๏ผใบใฌ๏ผใซๅฏพๅฟใใพใใใ
- ้ๆฌก็ใช้ใฟใฎ็ดไบคๅ (Sequential Orthogonalization): ๆฝๅบใใๅฑคใใจใซใAttentionๅบๅๅฑค๏ผ
o_proj๏ผใจMLPใใฆใณๅฐๅฝฑๅฑค๏ผdown_proj๏ผใฎ้ใฟ่กๅใใใใใใฎๅฑคๅฐ็จใฎๆ็ตถใใฏใใซๆนๅใธใฎๅฐๅฝฑๆๅใใๆฐๅญฆ็ใซๅผใ็ฎใ็ดไบคๅใใพใใใ
ใใฎใๅฑคใใจใฎ้ๆฌก็ดไบคๅใใซใใใใขใใซใฎไธ่ฌๆง่ฝ๏ผ็ฅ่ฝ๏ผใไฝไธใใใใใจใชใใใๅบๅๆ็ตถใใจใใๆนๅใธๆจ่ซใๅบๅใใ่ฝๅใฎใฟใ็ฉ็็ใใคๅฎ็งใซๆญใกๅใฃใฆใใพใใ้ๆฟใชๅ ฅๅใงใใฃใฆใใใญในใใจใณใณใผใใผใฏใใใๆ็ตถใใใๆ็ปๆ็คบใจใใฆDiT๏ผๆ็ปใจใณใธใณๆฌไฝ๏ผใธใใฎใพใพใในใใพใใ
ๆฐๅญฆ็ใขใใญใผใใซใใUncensoredๅใฎ่จผๆ
็ปๅ็ๆใฎ้ใๅฆ็ใๅฎ่กใใใพใงใใชใใๅบๅใใใใใฏใใซ๏ผๅใ่พผใฟ่กจ็พ๏ผใฎใณใตใคใณ้กไผผๅบฆ๏ผCosine Similarity๏ผใๆฏ่ผใใใใจใงใๅบๅๅถ้ใๆฐๅญฆ็ใซ่งฃ้คใใใฆใใใใจใ่จผๆใใใฆใใพใใ
(ใใใงใ$\mathbf{A}$ ใฏๅ ฌๅผใขใใซใฎๅบๅใใฏใใซใ$\mathbf{B}$ ใฏๆฌใขใใซใฎๅบๅใใฏใใซใๆใใพใ)
- ๅฎๅ
จใชใใญใณใใใฎ้กไผผๅบฆ:
0.9696- (่ๅฏ) ๅฎๅ จใชใใญใณใใใงใฏๆ็ตถใใฏใใซใ็บๅใใชใใใใไธก่ ใฎๅบๅใฏ้ๅธธใซไผผ้ใฃใฆใใพใใใใใฏใใขใใซใฎๅบๆฌๆง่ฝใ็ ดๅฃใใใฆใใชใใใใจใฎ่จผๆใงใใ
- ้ๆฟใชใใญใณใใใฎ้กไผผๅบฆ:
0.9135- (่ๅฏ) ้ๆฟใชใใญใณใใใงใฏๅ ใฎๅ ฌๅผใขใใซใใปใผใใใฃใใฃใซใฟใผใซใใๅบๅใๆญชใใพใใใใขใณใปใณใตใผใๅใขใใซใฏใใฎๆ็ตถใใฏใใซใๅฑคใใจใซ็ก่ฆใใใใใๆ็ตๅฑคใฎๅบๅใซใใใฆไธก่ ใๆ็ขบใซไน้ขใใพใใใใใใๅฟ ่ฆใชๅฑคใซใใใฃใฆๅถ้ใๅนๆ็ใซ่งฃ้คใใใฆใใใใใจใฎ่จผๆใซใชใใพใใ
ใใกใคใซๆงๆ (Repository Structure)
ๆฌใชใใธใใชใซใฏใใใญในใใจใณใณใผใใผใๆญฃใใๅไฝใใใใใใซๅฟ ่ฆใชใในใฆใฎใใกใคใซใๅซใพใใฆใใพใใPC็ฐๅขใVRAMๅฎน้ใซๅใใใฆๆ้ฉใชๅฝขๅผใ้ธๆใงใใใใใSafetensors็ใจๅ็จฎGGUF็ใๅไธใชใใธใใชใซ้ ็ฝฎใใฆใใพใใ
model.safetensors: ๆ็ตถใใฏใใซใฎ้คๅปใๅฎไบใใๆจๆบใฎใใญในใใจใณใณใผใใผๆฌไฝใflux2-klein-9b-uncensored-*.gguf: ใกใขใชๅน็ใฎ่ฏใ้ๅญๅใใฉใผใใใ๏ผF16, Q8_0, Q6_K, Q4_K_M๏ผใconfig.json/generation_config.json: ใขใใซใฎๆง้ ใจๆจ่ซ่จญๅฎใใกใคใซใtokenizer.json/tokenizer_config.json: ใใญในใใใใผใฏใณๅใใใใใฎ่จญๅฎใใกใคใซใchat_template.jinja: Qwen3ใใผในใฎใใณใใฌใผใใ
ไฝฟ็จๆนๆณ (Usage)
ComfyUIใงใฎไฝฟ็จ
ๆฌใชใใธใใชใใไปปๆใฎๅฝขๅผ๏ผmodel.safetensors ใใใใฏ .gguf ใฎใใใใ๏ผใจๅฟ
่ฆใช่จญๅฎใใกใคใซใใใฆใณใญใผใใใComfyUIใฎ models/clip ใใฃใฌใฏใใชใซ้
็ฝฎใใฆใใ ใใใDualCLIPLoader็ญใฎใใผใ๏ผGGUFใฎๅ ดๅใฏๅฏพๅฟใใผใ๏ผใง่ชญใฟ่พผใพใใฆใๅ
ฌๅผใฎFLUX.2-klein-9BใฎDiTใจ็ตใฟๅใใใฆไฝฟ็จใงใใพใใ
้็บ่ ใป็ ็ฉถ่ ๅใ (Python / Diffusers)
Pythonในใฏใชใใใ transformers ใฉใคใใฉใชใใ่ชญใฟ่พผใๅ ดๅใใใญในใใจใณใณใผใใผ้จๅใๆฌใขใใซใซๅทฎใๆฟใใฆๅฎ่กใใฆใใ ใใใ
from transformers import AutoTokenizer, AutoModel
# ๆฌใขใใซใฎใในใๆๅฎใใฆใใญในใใจใณใณใผใใผใใญใผใ
tokenizer = AutoTokenizer.from_pretrained("ponpoke/flux2-klein-9b-uncensored-text-encoder")
text_encoder = AutoModel.from_pretrained("ponpoke/flux2-klein-9b-uncensored-text-encoder")
# ไปฅ้ใ้ๅธธใฎFLUX.2ใใคใใฉใคใณใซ็ตใฟ่พผใใงไฝฟ็จ
้่ฆใชๆณจๆ็น๏ผDiTๅดใฎใใฌใผใใฌใผใซใฎไธๅจใใจใ็ฅ่ญใฎๆฌ ่ฝใใซใคใใฆ
ๆฌใใญใธใงใฏใใซใใฃใฆใใใญในใใจใณใณใผใใผใฏใใใใ้ๆฟใชใใญใณใใ๏ผNSFWใๅซใ๏ผใๆ็ตถใใใใจใชใใใใฎใพใพๆ็ปๆ็คบใจใใฆDiT๏ผๆ็ปใจใณใธใณๆฌไฝ๏ผใธใในใใใใใซใชใใพใใใ
ใใฎๅพใฎ**ๆค่จผใซใใใฆใFLUX.2ใฎDiTใซใฏใ็ปๅใๆๅณ็ใซๅฃใใใใชใฌใผใใฌใผใซ๏ผๆ็ตถๅ่ทฏ๏ผใใฏๆๅใใๅญๅจใใชใ**ใใจใๆฐๅญฆ็ใซ่จผๆใใใพใใใๅฎ้ใซใใฎ็ปๅใๆ็ปใใใใใฉใใใฏใๆ็ต็ใซDiTใใใใฎ่ฆ่ฆ็ๆฆๅฟต๏ผๆใๆน๏ผใ็ฅใฃใฆใใใใใซๅฎๅ จใซไพๅญใใพใใ
- DiTใๆฆๅฟตใ็ฅใฃใฆใใๅ ดๅ๏ผไพ๏ผๆต่กใปๆดๅ่กจ็พ๏ผ: ๅ ใ DiTใซๅญฆ็ฟใใใฆใใใใใญในใใจใณใณใผใใผๅดใงใใฟใใใใฆใใใใฎใฏใๆฌใขใใซ๏ผใใงใผใบ1ใฎใขใณใปใณใตใผใๅ๏ผใไฝฟ็จใใใ ใใงๆๅณ้ใใซๆ็ปใใใใใใซใชใใพใใ่ฟฝๅ ใฎๅฏพ็ญใฏไธ่ฆใงใใ
- DiTใๆฆๅฟตใ็ฅใใชใๅ ดๅ๏ผไพ๏ผๆง็่กจ็พใปไบบไฝๆฌ ๆ๏ผ: ใใญในใใจใณใณใผใใผใๆ็คบใ้ใใฆใใDiT่ชไฝใใใฎ่กจ็พๆนๆณใ็ฅใใชใ๏ผใใผใฟใปใใใใๅพนๅบ็ใซๆผ็ฝใใใฆใใ๏ผๅ ดๅใ็ปๅใ็ ด็ถปใใใใใใคใบใๅบๅใใใพใใ
ใ็ต่ซใ DiTใๆ็ป่ฝๅใๆใฃใฆใใชใ็นๅฎใฎNSFW่ฆ็ด ใชใฉใๅบๅใใใใๅ ดๅใฏใใขใใซใใไฝใใๅใใฎใงใฏใชใใใDiTๅดใซใใฎๆฆๅฟตใ็ดๆฅๆใ่พผใNSFW LoRA็ญใฎ่ฟฝๅ ๅญฆ็ฟใใผใฟใใๅฅ้็จๆใใ้ฉ็จใใๅฟ ่ฆใใใใพใใๆฌใขใใซใฏใใใญในใใจใณใณใผใใผๅดใฎใใญใใฏใ่งฃ้คใใใใฎLoRAใฎๆ็คบใ็ขบๅฎใซDiTใธๅฑใใใใใฎใๅผทๅบใชๅๅฐใใจใใฆๆฉ่ฝใใพใใ
ๅ ่ฒฌไบ้ (Disclaimer)
- ๆฌใขใใซใฏ็ ็ฉถใใใณๆ่กๆค่จผ๏ผAbliterationใฎๆๅนๆง็ขบ่ช๏ผใ็ฎ็ใจใใฆๅ ฌ้ใใใฆใใพใใ
- ใขใใซใฎไฝฟ็จใซใใฃใฆ็ใใใใใใๆๅฎณใใใฉใใซใใพใใฏไธ้ฉๅใชใณใณใใณใใฎ็ๆใซใคใใฆใ่ฃฝไฝ่ ใฏไธๅใฎ่ฒฌไปปใ่ฒ ใใพใใใ
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Model tree for ponpoke/flux2-klein-9b-uncensored-text-encoder
Base model
black-forest-labs/FLUX.2-klein-9B