Instructions to use vbius01/est-roberta-ud-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vbius01/est-roberta-ud-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vbius01/est-roberta-ud-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("vbius01/est-roberta-ud-ner") model = AutoModelForTokenClassification.from_pretrained("vbius01/est-roberta-ud-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from vbius01/est-roberta-ud-ner: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/vbius01/est-roberta-ud-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://vbius01/est-roberta-ud-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/vbius01/est-roberta-ud-ner/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 32cb5b9fdfe1e649d1af64b5daae01137e5378cc2cd399f9bec917f6b2d49f0d
- Size of remote file:
- 5.37 kB
- SHA256:
- 6d46d869b19d5d2c4a64435a2a7cae898dbe3aa17a08988fd66872903e558cd0
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