Update README.md

README.md

@@ -2,7 +2,8 @@
 license: mit
 library_name: transformers
 widget:
-- src: https://fema-cap-imagery.s3.amazonaws.com/Images/CAP_-_Flooding_Spring_2023/Source/IAWG_23-B-5061/A0005/D75_0793_DxO_PL6_P.jpg
+- src: >-
+    https://fema-cap-imagery.s3.amazonaws.com/Images/CAP_-_Flooding_Spring_2023/Source/IAWG_23-B-5061/A0005/D75_0793_DxO_PL6_P.jpg
 - example_title: Example classification of flooded scene
 pipeline_tag: image-classification
 tags:
@@ -10,9 +11,11 @@ tags:
 - Aerial Imagery
 - Disaster Response
 - Emergency Management
+datasets:
+- MITLL/LADI-v2-dataset
 ---
 # Model Card for MITLL/LADI-v2-classifier-small-reference
-LADI-v2-classifier-small-reference is based on [google/bit-50](https://huggingface.co/google/bit-50) and fine-tuned on the LADI v2_resized dataset. LADI-v2-classifier is trained to identify labels of interest to disaster response managers from aerial images.
+LADI-v2-classifier-small-reference is based on [google/bit-50](https://huggingface.co/google/bit-50) and fine-tuned on the [MITLL/LADI-v2-dataset](https://huggingface.co/datasets/MITLL/LADI-v2-dataset). LADI-v2-classifier is trained to identify labels of interest to disaster response managers from aerial images.
 
 🔴 __IMPORTANT__ ❗🔴 This model is the 'reference' version of the model, which is trained on 80% of the 10,000 available images. It is provided to facilitate reproduction of our paper and is not intended to be used in deployment. For deployment, see the [MITLL/LADI-v2-classifier-small](https://huggingface.co/MITLL/LADI-v2-classifier-small) and [MITLL/LADI-v2-classifier-large](https://huggingface.co/MITLL/LADI-v2-classifier-large) models, which are trained on the full LADI v2 dataset (all splits).