Instructions to use RobW/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RobW/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RobW/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RobW/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("RobW/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from RobW/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/RobW/bert-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://RobW/bert-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/RobW/bert-finetuned-ner/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 9264f72dcbac2cf88073d36d383f42e311bc5c36c7472dbf1288b73df90280b3
- Size of remote file:
- 5.18 kB
- SHA256:
- 19019b9597de8d71d4a6428c223cb99745337b7981090d5e6beca996daeafe90
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