Instructions to use suyagi/Resnet50-Isic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use suyagi/Resnet50-Isic with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://suyagi/Resnet50-Isic") - Notebooks
- Google Colab
- Kaggle
Upload model_resnet.keras
Browse files- .gitattributes +1 -0
- model_resnet.keras +3 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
model_resnet.keras filter=lfs diff=lfs merge=lfs -text
|
model_resnet.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2926dfaba446252728e0561bf43389e0edff7c92c8ecbee42996cfd68fc62ea4
|
| 3 |
+
size 223963966
|