Instructions to use webmichaelnosenko/rust-bert-base-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use webmichaelnosenko/rust-bert-base-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="webmichaelnosenko/rust-bert-base-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("webmichaelnosenko/rust-bert-base-NER") model = AutoModelForTokenClassification.from_pretrained("webmichaelnosenko/rust-bert-base-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 049a8736e3d4ababc4dea768bf6c697dd814646b2c7d8bd2cf8948a18f935fa4
- Size of remote file:
- 433 MB
- SHA256:
- 82d43cb923be1400ab7c7537ecd86f29daa5fd3b6340a043e65b96247cb95f72
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