Instructions to use dantedgp/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dantedgp/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dantedgp/bert-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dantedgp/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("dantedgp/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dantedgp/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/dantedgp/bert-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://dantedgp/bert-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dantedgp/bert-finetuned-ner/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- dfb407423b1909624fe3b7d9708ad81ef6ced5982885da9e03d77227b90b2fc6
- Size of remote file:
- 5.11 kB
- SHA256:
- 5f7c1b7247891408de54395ba90f80d0a15d2c67f8f9771b65e2a4bff7703a5a
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