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
Update README.md
Browse files
README.md
CHANGED
|
@@ -8,6 +8,7 @@ library_name: keras
|
|
| 8 |
pipeline_tag: image-classification
|
| 9 |
tags:
|
| 10 |
- biology
|
|
|
|
| 11 |
datasets:
|
| 12 |
- thangved/zitwaste
|
| 13 |
---
|
|
|
|
| 8 |
pipeline_tag: image-classification
|
| 9 |
tags:
|
| 10 |
- biology
|
| 11 |
+
- chemistry
|
| 12 |
datasets:
|
| 13 |
- thangved/zitwaste
|
| 14 |
---
|