Instructions to use Eakempreet/ATAS-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Eakempreet/ATAS-models with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://Eakempreet/ATAS-models") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
atas_final_hit_classifier_model.joblib
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d4a4900f2e5e1a4027d6652ff605e363f5c79a97abb640aba09708d6792a78c1
|
| 3 |
+
size 425666
|