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:
- 6b717a8a3547b66554cb607c92acad3a069a5b7bdac22157af50c9319104918e
- Size of remote file:
- 809 kB
- SHA256:
- b47e2bf95c06d31f66d912fc82e0867c2ef0d085686bef45835a07a484cbcd21
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.