Instructions to use Yuhthe/ner-bert-base-phoner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yuhthe/ner-bert-base-phoner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Yuhthe/ner-bert-base-phoner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Yuhthe/ner-bert-base-phoner") model = AutoModelForTokenClassification.from_pretrained("Yuhthe/ner-bert-base-phoner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Yuhthe/ner-bert-base-phoner: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/Yuhthe/ner-bert-base-phoner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Yuhthe/ner-bert-base-phoner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Yuhthe/ner-bert-base-phoner/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- b95b8f58c03ce10300af3c2aca73fd55959f20b057fabf8dce462b417cb8613c
- Size of remote file:
- 496 MB
- SHA256:
- 8a7ef49949351ebf689717ceae7cb2783732af734e93347739798f29dda36516
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