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An adult photographic-content LoRA for MOSS-Image-SFT or MOSS-Image-Base, with **MOSS-Image-SFT preferred for inference**. It is tuned for explicit adult portraiture, nude poses, indoor scenes, and close photographic compositions. The repository-root adapter is now the focused 1,750-step checkpoint trained on 130 images; start at scale `0.8`. The former 2,000-step, 221-image adapter is preserved under `original-checkpoint-2000/` and remains available at its recommended scale of `0.7`. A GGUF conversion (44% less VRAM on Q8 and 66% less VRAM on Q4) is also available here: https://huggingface.co/axiomofmind/Moss-image-nsfw-uncensored-lora-GGUF which can be used with MOSS-Image-SFT-GGUF

Image generation
Input Text→ Output Image
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Separate F16 GGUF conversions of the adult-photography LoRAs from axiomofmind/Moss-image-nsfw-uncensored-lora. They are designed to be applied at inference time to axiomofmind/Moss-Image-SFT-GGUF, keeping the adapter strength adjustable without creating a merged model for every base quantization or scale. This repository contains the **LoRA adapter only**. It does not contain the base diffusion transformer, Qwen3.5 text encoder, tokenizer, or VAE. > **Adult-content notice:** The source adapter is intended for lawful creative generation involving clearly adult fictional subjects and can produce explicit sexual imagery. It is for adults only in jurisdictions where such content is lawful. Do not use it for minors or age-ambiguous subjects, abuse, exploitation, coercion, non-consensual imagery, or sexualized depictions of identifiable real people without explicit consent.

Image generation
Input Text→ Output Image
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Unofficial GGUF conversions of OpenMOSS-Team/MOSS-Image-SFT, a 5B text-to-image diffusion transformer fine-tuned from MOSS-Image-Base. These files contain the **diffusion transformer (DiT) only**. They still require a Qwen3.5-9B text encoder, the official MOSS tokenizer, and the MOSS / FLUX.2 VAE. They are image-model GGUFs for compatible diffusion runtimes—not text LLMs for Ollama, LM Studio, or llama.cpp text generation. Both are GGUF v3 files with 463 tensors and `general.architecture=moss_image` metadata. Checksums are also provided in `SHA256SUMS`.

Image generation
Input Text→ Output Image
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Source / docs ↗
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