Update README.md

README.md

@@ -2,6 +2,10 @@
 tags:
 - model_hub_mixin
 - pytorch_model_hub_mixin
+license: mit
+datasets:
+- Artificio/WikiArt
+pipeline_tag: unconditional-image-generation
 ---
 
 This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
@@ -37,7 +41,7 @@ The model has three variants:
   - S: single RTX 4060ti 16G for 24 hrs,
   - B: single RTX 4060ti 16G for 90 hrs,
   - L: single RTX 4090D 24G for 48 hrs, followed by single RTX 4060ti 16G for 100 hrs. 
-- loss curve: all variants witnessed a dramatic loss in the first epoch from above 1.0000 to around 0.2000, followed by a much slower decrease to finally reach loss=0.1600 at 20th epoch. DiT-S finally reached 0.1590; DiT-B finally reached 0.1525; DiT-L finally reached 0.1500.
+- loss curve: all variants witnessed a dramatic loss in the first epoch from above 1.0000 to around 0.2000, followed by a much slower decrease to finally reach loss=0.1600 at 20th epoch. DiT-S finally reached 0.1590; DiT-B finally reached 0.1525; DiT-L finally reached 0.1510.
 
 ### Performance and Limitations
 - The models demonstrates basic abilities to understand genres and styles and produce visually-appealing paintings (at first glance).