Instructions to use LibrAI/longformer-action-ro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LibrAI/longformer-action-ro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LibrAI/longformer-action-ro")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LibrAI/longformer-action-ro") model = AutoModelForSequenceClassification.from_pretrained("LibrAI/longformer-action-ro") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4cdc0188e1a5e8aa09fdfa3d7c6b055c4302e2986843e5e03ebe55831a7f7e4e
- Size of remote file:
- 595 MB
- SHA256:
- c4d3e8d173485717cc4ab12a58a7f4c425535c1aab9fc2f978dc7f35b8091419
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