Instructions to use Aimlab/Roberta-Base-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aimlab/Roberta-Base-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Aimlab/Roberta-Base-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Aimlab/Roberta-Base-NER") model = AutoModelForTokenClassification.from_pretrained("Aimlab/Roberta-Base-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 499db2aef5c4d616513d99c40c116a5129ed2d372ece0ac2bc0bce533fa67a9e
- Size of remote file:
- 1.11 GB
- SHA256:
- 15149b506770f2fffcc030115fee8eb9d34dc131f5aed627b5e857116fae62a6
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