Instructions to use OpenLab-NLP/openlem2-retrieval-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use OpenLab-NLP/openlem2-retrieval-qa 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-retrieval-qa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5b7eff01785cf00934b32dd54c295f8170f0bdf69ec719a2745bb19a11bfd29
- Size of remote file:
- 84.6 MB
- SHA256:
- c40264321ca291c142cda04d929445f915993d28713271f18569907e8a411e70
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.