Instructions to use Jed612/encoder-BLSTM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use Jed612/encoder-BLSTM with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("Jed612/encoder-BLSTM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd591cc777e14f78301831b5b284221950a7ae5946b37d21c7bccc423a9a4670
- Size of remote file:
- 55 Bytes
- SHA256:
- 737e5c4d7f338206b8d34ae921258926fc7e93140b02a1d5d6da23ace0a639e0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.