Instructions to use radmada/FinBERT-BaseVocab-Uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radmada/FinBERT-BaseVocab-Uncased with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("radmada/FinBERT-BaseVocab-Uncased", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e19ed3251ad5a78671dee82af282844b8ebcff0ff4c36bd3258e64294285299
- Size of remote file:
- 440 MB
- SHA256:
- 5f88f5cd36ae1256392d23ceabd667ce831419e141da4db4c3c61db7e7245ae3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.