Instructions to use Tirendaz/roberta-base-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tirendaz/roberta-base-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tirendaz/roberta-base-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tirendaz/roberta-base-NER") model = AutoModelForTokenClassification.from_pretrained("Tirendaz/roberta-base-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e9eb1627e897e8be2b86278bf3c114e415f2e5a009ad9e6da9d55751835b0a1
- Size of remote file:
- 4.03 kB
- SHA256:
- a78dfdbf99d450593b49611291fd08d3bf1c84b4a780cac5dd8134e3be9860df
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.