Instructions to use pawlo2013/roberta-nerc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pawlo2013/roberta-nerc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pawlo2013/roberta-nerc")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pawlo2013/roberta-nerc") model = AutoModelForTokenClassification.from_pretrained("pawlo2013/roberta-nerc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eaba30c339855ea1f6301bd7d360e1c5c5ca83a954259140145a622c1a2e3c23
- Size of remote file:
- 496 MB
- SHA256:
- 184b948ccd52b2fd4f1d9c687bbc183e009684c785ee5df73443a0fe7c5660a1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.