Instructions to use raulgdp/bert-base-case-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raulgdp/bert-base-case-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="raulgdp/bert-base-case-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("raulgdp/bert-base-case-ner") model = AutoModelForTokenClassification.from_pretrained("raulgdp/bert-base-case-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from raulgdp/bert-base-case-ner: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/raulgdp/bert-base-case-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://raulgdp/bert-base-case-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/raulgdp/bert-base-case-ner/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- bd28ec755edc5e13e9cf743f6d74e679b303cea13cd83a3b00b228f524f9635d
- Size of remote file:
- 4.54 kB
- SHA256:
- a22e4fd86fde862845025ac4f536d98b8a7c04f0183804f37c9e9a1f9840c1f7
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