Instructions to use rdetch22/model_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rdetch22/model_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rdetch22/model_ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rdetch22/model_ner") model = AutoModelForTokenClassification.from_pretrained("rdetch22/model_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2e3419daebc9c0d04226b15c203027ed974ff1529ac4152b6ce7a60d33291be
- Size of remote file:
- 440 MB
- SHA256:
- 9a613db45d618288eb16ae286b8b108f7050dd2e3810ade6e71b029196df5574
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.