Update model card

README.md

@@ -1,21 +1,32 @@
 ---
 library_name: diffusers
+pipeline_tag: image-to-image
 tags:
 - dit4sr
 - super-resolution
 - diffusion-transformer
 base_model: stabilityai/stable-diffusion-3.5-medium
 ---
-# dit4sr-replication
+# DiT4SR Replication
 
-This repository contains the `checkpoint-150000` export from the local DiT4SR experiment `dit4sr-replication`.
+This repository contains the DiT4SR transformer weights exported from the local `dit4sr-replication` experiment at `checkpoint-150000`.
 
-## Included files
+## 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.
 
-## Loading
+## 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
@@ -23,4 +34,10 @@ 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 this repository's README.
+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/`