Instructions to use ademaulana/CNN-ASL-Alphabet-Sign-Recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ademaulana/CNN-ASL-Alphabet-Sign-Recognition with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://ademaulana/CNN-ASL-Alphabet-Sign-Recognition") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcfefaf69713efe25f1ca556cb918e6d3cce4442616d3a2d02d197a1f26c2b78
- Size of remote file:
- 3.14 MB
- SHA256:
- 3499939aba14ee69ee36983de9c01a5f6d5b9d04340fb9a5abc96f82726a71be
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.