Instructions to use izaitova/ner_be with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use izaitova/ner_be with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="izaitova/ner_be")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("izaitova/ner_be") model = AutoModelForTokenClassification.from_pretrained("izaitova/ner_be", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from izaitova/ner_be: direct link, hf CLI and curl.
- Browser
- Download file 4.46 kB
-
https://huggingface.co/izaitova/ner_be/resolve/main/training_args.bin
- Command line
-
hf download hf://izaitova/ner_be/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/izaitova/ner_be/resolve/main/training_args.bin
4.46 kB
- Xet hash:
- e6a033173032fd4547ed79f9d2d1b9b4e04a7e55a1f377d6500d2e4a7879330e
- Size of remote file:
- 4.46 kB
- SHA256:
- 1a186a765b8b58063fcb1210936cd93c44c532ea8c793635623863a781a060d7
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