Instructions to use thangved/zitwaste with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use thangved/zitwaste with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://thangved/zitwaste") - Notebooks
- Google Colab
- Kaggle
Upload model.keras
Browse files- model.keras +2 -2
model.keras
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:128ea94b0be3683832ae695b1c33ccf2cdb1ec9046b8ceff10ef7849166a9417
|
| 3 |
+
size 12123640
|