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
Download bpe.model from OpenLab-NLP/openlem2: direct link, hf CLI and curl.
- Browser
- Download file 804 kB
-
https://huggingface.co/OpenLab-NLP/openlem2/resolve/main/bpe.model
- Command line
-
hf download hf://OpenLab-NLP/openlem2/bpe.model
-
curl -L -o bpe.model https://huggingface.co/OpenLab-NLP/openlem2/resolve/main/bpe.model
804 kB
- Xet hash:
- 113588c57e1720b0e7197b5084703ab7f74e60026af25d7aff46b269b074dc15
- Size of remote file:
- 804 kB
- SHA256:
- 0f4525461e6dce6868f700d24ef820cd26a1f56097e4073a72966a8294fdcd80
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