Instructions to use lyfforever/bert-finetuned-ner4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lyfforever/bert-finetuned-ner4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lyfforever/bert-finetuned-ner4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lyfforever/bert-finetuned-ner4") model = AutoModelForSequenceClassification.from_pretrained("lyfforever/bert-finetuned-ner4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d43c0c18d0f0ea886bc6e07fb8a2f58d1d9c8adb3759d6e514933a088fc87d3
- Size of remote file:
- 433 MB
- SHA256:
- 4b2c0c4732f12487239b153ead279959b76a85c7495787c121c4782de4584390
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.