Instructions to use yubol/bert-finetuned-ner-30 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yubol/bert-finetuned-ner-30 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="yubol/bert-finetuned-ner-30")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("yubol/bert-finetuned-ner-30") model = AutoModelForTokenClassification.from_pretrained("yubol/bert-finetuned-ner-30", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06639b4be5d4d1279753ac14643a4f48f3c0e82652fecf8cca252756df3e7170
- Size of remote file:
- 431 MB
- SHA256:
- 168bd894cd2e495d4063ab3f0b9e274c745e599def10a34f1bf1bb1dc3e34e3a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.