Instructions to use data-archetype/moss_image_base_dmd2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use data-archetype/moss_image_base_dmd2 with PEFT:
Task type is invalid.
- Diffusers
How to use data-archetype/moss_image_base_dmd2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OpenMOSS-Team/MOSS-Image-Base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("data-archetype/moss_image_base_dmd2") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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# moss_image_base_dmd2
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An 8-step LoRA (rank 128) for [MOSS-Image-Base](https://huggingface.co/OpenMOSS-Team/MOSS-Image-Base), distilled by distribution
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matching
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50 guided steps.
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(FLUX.2 small decoder), tokenizer and inference pipeline are MOSS-Image-Base's,
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unchanged. How it was trained is in [TECH_REPORT.md](TECH_REPORT.md).
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It was trained on MOSS-Image-Base, but should work with most fine-tunes of it and with
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other LoRAs: load it alongside them, at strength 1.
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| `workflows/moss_image_base_dmd2_8step_api.json` | The same workflow in ComfyUI's API format |
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Both LoRA files make the same weight change; the ComfyUI file packs each block's q, k and v
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LoRAs into one
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## Sampling
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# moss_image_base_dmd2
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An 8-step LoRA (rank 128) for [MOSS-Image-Base](https://huggingface.co/OpenMOSS-Team/MOSS-Image-Base), distilled by distribution
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matching. Inference is 8 forwards at CFG 1, without a negative prompt, in place of the base model's
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50 guided steps. Training details in [TECH_REPORT.md](TECH_REPORT.md).
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It was trained on MOSS-Image-Base, but should work with most fine-tunes of it and with
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other LoRAs: load it alongside them, at strength 1.
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| `workflows/moss_image_base_dmd2_8step_api.json` | The same workflow in ComfyUI's API format |
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Both LoRA files make the same weight change; the ComfyUI file packs each block's q, k and v
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LoRAs into one equivalent LoRA on ComfyUI's fused `qkv` projection.
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## Sampling
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