Instructions to use khoaliamle/Rust_Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use khoaliamle/Rust_Detection with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://khoaliamle/Rust_Detection") - Notebooks
- Google Colab
- Kaggle
Dang Khoa Le commited on
Upload rust_cnn_model.h5
Browse files- rust_cnn_model.h5 +3 -0
rust_cnn_model.h5
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:baa26df9f8335eac426b6192ea5cb96d96fcac3d7a0652cd705356518ccb91cf
|
| 3 |
+
size 4198600
|