Instructions to use danasone/rubert-tiny-essay with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danasone/rubert-tiny-essay with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="danasone/rubert-tiny-essay")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("danasone/rubert-tiny-essay") model = AutoModelForTokenClassification.from_pretrained("danasone/rubert-tiny-essay") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6ff2dc3cbd3f9a646cd4d338b990c21dce1c34198fa489e4d926784bded34f3
- Size of remote file:
- 116 MB
- SHA256:
- 98705e0bbf076af38b65155502020cedb473e77922067f8ebbcc15a26698d890
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