ImageSuperResolution Replication

--- library_name: diffusers pipeline_tag: image-to-image tags: - dit4sr - super-resolution - diffusion-transformer base_model: stabilityai/stable-diffusion-3.5-medium --- # DiT4SR Replication This repository contains the DiT4SR transformer weights exported from the local `dit4sr-replication` experiment at `checkpoint-150000`. ## What This Repo Contains This Hugging Face repo publishes only the `transformer/` checkpoint used by `SD3Transformer2DModel`. It does not include the full Stable Diffusion 3.5 base model, tokenizers, schedulers, or the rest of the DiT4SR inference stack. ## Files - `transformer/` contains the publishable model weights and config. - `source_checkpoint.json` records the local source path and checkpoint name used for the upload. ## Checkpoint Metadata - Experiment: `dit4sr-replication` - Source checkpoint: `checkpoint-150000` - Published artifact: transformer weights only ## Loading In DiT4SR ```python from model_dit4sr.transformer_sd3 import SD3Transformer2DModel model = SD3Transformer2DModel.from_pretrained("NisargUpadhyay/ImageSuperResolution-replication", subfolder="transformer") ``` You still need the rest of the DiT4SR codebase and the base SD3 assets described in the project README. ## Related Resources - Project repo: `NisargUpadhyayIITJ/Deep-Learning-Course-Project` - Training/evaluation dataset repo: `NisargUpadhyay/ImageSuperResolution` - Matching training subset in the dataset repo: `Replication/`

Source context: 0 downloads · 0 likes · Pipeline image-to-image · Library diffusers · Repo NisargUpadhyay/ImageSuperResolution-replication