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:
# !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://OpenLab-NLP/openlem2") - Notebooks
- Google Colab
- Kaggle
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Download README.md from OpenLab-NLP/openlem2: direct link, hf CLI and curl.
- Browser
- Download file 159 Bytes
-
https://huggingface.co/OpenLab-NLP/openlem2/resolve/main/README.md
- Command line
-
hf download hf://OpenLab-NLP/openlem2/README.md
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curl -L -o README.md https://huggingface.co/OpenLab-NLP/openlem2/resolve/main/README.md
159 Bytes
metadata
license: apache-2.0
datasets:
- OpenLab-NLP/ko-corpus
language:
- ko
pipeline_tag: sentence-similarity
tags:
- sentence
- embedding
library_name: keras