Instructions to use EffyLi/bert-base-NER-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EffyLi/bert-base-NER-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EffyLi/bert-base-NER-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EffyLi/bert-base-NER-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("EffyLi/bert-base-NER-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from EffyLi/bert-base-NER-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/EffyLi/bert-base-NER-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://EffyLi/bert-base-NER-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/EffyLi/bert-base-NER-finetuned-ner/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 64dcb20078eecf2457a8a21566c7ae750bdd4786368e0887d6a1956fcfd606c2
- Size of remote file:
- 3.06 kB
- SHA256:
- c3533ea875010b1f4cda973ab1b6e122b9b880dfa0052bc0a10161142ab2a4d0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.