Update README.md

README.md

@@ -19,7 +19,7 @@ widget:
   example_title: debris
 ---
 
-# Model card for wide_resnet50_2.tiatoolbox-kather100k
+# Model card for wide_resnet101_2.tiatoolbox-kather100k
 
 A Wide-ResNet-B image classification model. \
 Trained by [Tissue Image Analytics (TIA) Centre](https://warwick.ac.uk/fac/cross_fac/tia/) on "kather100k" histology patches.
@@ -30,7 +30,7 @@ Trained by [Tissue Image Analytics (TIA) Centre](https://warwick.ac.uk/fac/cross
 
 - **Model Type:** Image classification / Feature backbone
 - **Model Stats:**
-  - Params (M): 66.9
+  - Params (M): 125.0
   - Image size: 224 x 224 x 3
 - **Dataset**: [kather100k](https://tia-toolbox.readthedocs.io/en/latest/_autosummary/tiatoolbox.models.dataset.info.KatherPatchDataset.html#tiatoolbox.models.dataset.info.KatherPatchDataset), also called NCT-CRC-HE
 - **Original:** https://github.com/TissueImageAnalytics/tiatoolbox
@@ -54,7 +54,7 @@ img = Image.open(
 
 # load model from the hub
 model = timm.create_model(
-  model_name="hf-hub:1aurent/wide_resnet50_2.tiatoolbox-kather100k",
+  model_name="hf-hub:1aurent/wide_resnet101_2.tiatoolbox-kather100k",
   pretrained=True,
 ).eval()
 
@@ -82,7 +82,7 @@ img = Image.open(
 
 # load model from the hub
 model = timm.create_model(
-  model_name="hf-hub:1aurent/wide_resnet50_2.tiatoolbox-kather100k",
+  model_name="hf-hub:1aurent/wide_resnet101_2.tiatoolbox-kather100k",
   pretrained=True,
   num_classes=0,
 ).eval()