Instructions to use venkatpr/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use venkatpr/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="venkatpr/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("venkatpr/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("venkatpr/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd6a729c7b8ce5f8a36b6d9abba026d01c900fae533d7a9bdc56c849b6c3dadf
- Size of remote file:
- 431 MB
- SHA256:
- 4c6b96b88ef48f77c3992f3ced2b0179f31e3e28bee834aaa812646c4cfb0248
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.