Instructions to use Andrija/M-bert-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andrija/M-bert-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Andrija/M-bert-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Andrija/M-bert-NER") model = AutoModelForTokenClassification.from_pretrained("Andrija/M-bert-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Andrija/M-bert-NER: direct link, hf CLI and curl.
- Browser
- Download file 2.61 kB
-
https://huggingface.co/Andrija/M-bert-NER/resolve/main/training_args.bin
- Command line
-
hf download hf://Andrija/M-bert-NER/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Andrija/M-bert-NER/resolve/main/training_args.bin
2.61 kB
- Xet hash:
- d7770e3b4b651e70d0499c36919cfcda9f412aa73c6c7a1f238c236b5149f98a
- Size of remote file:
- 2.61 kB
- SHA256:
- 6fa2748d6d0237526a4fca28df742f9fac2ec813b632fbc0ead5fee9468dfac0
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