Instructions to use jurabi/bert-ner-japanese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jurabi/bert-ner-japanese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jurabi/bert-ner-japanese")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jurabi/bert-ner-japanese") model = AutoModelForTokenClassification.from_pretrained("jurabi/bert-ner-japanese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jurabi/bert-ner-japanese: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/jurabi/bert-ner-japanese/resolve/main/training_args.bin
- Command line
-
hf download hf://jurabi/bert-ner-japanese/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jurabi/bert-ner-japanese/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 43755d5ed71f1fcb183c702275da5ac3f31e5c9dcb045c79735f08a2203fc978
- Size of remote file:
- 3.38 kB
- SHA256:
- af5169cc5cd8695dfbb4590261fadb2c4876a3e82a537eb9c20215ab28ca587c
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