Instructions to use LibrAI/bert-action-ro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LibrAI/bert-action-ro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LibrAI/bert-action-ro")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LibrAI/bert-action-ro") model = AutoModelForSequenceClassification.from_pretrained("LibrAI/bert-action-ro") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d56e1f95549198f2f3d475ee9a5dc298be2bf21ecfee19e0bdc92c9ac77105fe
- Size of remote file:
- 433 MB
- SHA256:
- e4d565d4d0f3628d60e1aeabc22ede3861d2535d5e8557df3e0114b70e11c677
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