Instructions to use Miladsaeedi70/bert-finetuned-ner-tokenclass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Miladsaeedi70/bert-finetuned-ner-tokenclass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Miladsaeedi70/bert-finetuned-ner-tokenclass")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Miladsaeedi70/bert-finetuned-ner-tokenclass") model = AutoModelForTokenClassification.from_pretrained("Miladsaeedi70/bert-finetuned-ner-tokenclass", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe36fd80f3f1ee902c7ed5297eaec7286172f015da5db47dd331c2e722804b2f
- Size of remote file:
- 5.37 kB
- SHA256:
- e5597bffd62ab54b46ef82827ddd7591a4d65b26bf676c1af26d6c2af5ac5dba
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.