Instructions to use thangvip/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thangvip/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="thangvip/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("thangvip/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("thangvip/bert-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 692aeb88607c6d12b7ee43993b963aea1572c5d07da852c704557e1be6305263
- Size of remote file:
- 4.03 kB
- SHA256:
- d3493b00b11c71f2f3b27ee2b83bb71b5d6b2daefebda575bad47104def11189
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.