Instructions to use grexit-d/multipride_umberto_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use grexit-d/multipride_umberto_ner with Transformers:
# Load model directly from transformers import UmBERToWithNER model = UmBERToWithNER.from_pretrained("grexit-d/multipride_umberto_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a98e2c94d5c278cdb19fa186fb744f410b58d69da501b65e06da136d4036e72
- Size of remote file:
- 443 MB
- SHA256:
- 86d237b9c8643bb20cec0e16e96b9f2ca1c3605e1dac4429d1a94cbfbd8f718f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.