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model_index.json: pipeline/component registry (RSEditDiTChannelConcatPipeline).pipeline.py: custom local pipeline implementation used for inference/loading.checkpoint-30000/: training-state snapshot at step 30k (includes optimizer/scheduler/random states and transformer checkpoint).transformer/, vae/, text_encoder/, tokenizer/, scheduler/: exported model components for direct pipeline loading.logs/: experiment logs (logs/rsedit-dit/...).1from diffusers import DiffusionPipeline
2
3model_dir = "path/to/model"
4pipe = DiffusionPipeline.from_pretrained(model_dir, trust_remote_code=True)
5pipe = pipe.to("cuda")checkpoint-30000/optimizer.bin is large and is only needed to resume training, not for inference.pipeline.py and model_index.json in sync if the custom pipeline class name changes.