Chroma1-HD is an **8.9B** parameter text-to-image foundational model based on **FLUX.1-schnell**. It is fully **Apache 2.0 licensed**, ensuring that anyone can use, modify, and build upon it. As a **base model**, Chroma1 is intentionally designed to be an excellent starting point for **finetuning**. It provides a strong, neutral foundation for developers, researchers, and artists to create specialized models. for the fast CFG "baked" version please go to Chroma1-Flash.

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Kromoss

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Kromoss is a full fine-tune of MOSS-Image-Base at 1024 px. It uses the same architecture, inference pipeline, text encoder (Qwen3.5-9B) and VAE (FLUX.2 small decoder) as MOSS-Image-SFT, and this repo has the same layout, so it is a drop-in replacement. The repo also ships two 8-step turbo LoRAs distilled from MOSS-Image-Base: **8 steps, CFG 1**, no negative branch. - `8-steps-dmd2-lora.safetensors` (recommended): the DMD LoRA below, further trained with DMD2's GAN stage against real images. Slightly more contrast and detail, and the best PartiPrompts score. - `8-steps-dmd-lora.safetensors`: data-space DMD distillation. The transformer and text encoder use bfloat16; the VAE and initial noise use float32.

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MOSS-Image-Base-8-steps-dmd

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Work-in-progress distillation of OpenMOSS-Team/MOSS-Image-Base (50 steps, CFG 3) to 8 network evaluations, no CFG. Data-space DMD (arXiv 2610.12102): the generator iterates on its own clean estimate from fixed noise. Trained on compact-JSON `scene_graph` captions. Load `lora.safetensors` on the stock MOSS-Image-Base transformer (e.g. a ComfyUI LoRA loader, strength 1) and sample with the model's usual flow-matching Euler sampler, shift 5, **CFG 1**, 4-8 steps. Nothing else from this repo is needed. `transformer/` is a stock `MOSSImageTransformer` (load it with the release `pipeline_moss_image.py`); the text encoder, tokenizer and VAE are the base repo's.

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MOSS-Image-SFT-8-steps-dmd

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Work-in-progress distillation of OpenMOSS-Team/MOSS-Image-SFT (50 steps, CFG 3) to 8 network evaluations, no CFG. Data-space DMD (arXiv 2610.12102): the generator iterates on its own clean estimate from fixed noise. Trained on compact-JSON `scene_graph` captions. load lora.safetensors (at 1 strength recommended) or lora_latest.safetensors (at 0.7 strength recommended) directly to your comfyui lora loader `transformer/` is a stock `MOSSImageTransformer` (load it with the release `pipeline_moss_image.py`); the text encoder, tokenizer and VAE are the base repo's.

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