Instructions to use OpenLab-NLP/openlem2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use OpenLab-NLP/openlem2 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://OpenLab-NLP/openlem2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4f4b50f45e6262a7a4ac832e5463bf4c612a27f3617671509ce93044d31a30b
- Size of remote file:
- 60.4 MB
- SHA256:
- 661d333eefe00a80fa9ffa38a4e9e07dab328988195c16cb05f5d816b643eb22
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.