Instructions to use lfcc/lusa_events with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lfcc/lusa_events with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="lfcc/lusa_events")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("lfcc/lusa_events") model = AutoModelForTokenClassification.from_pretrained("lfcc/lusa_events", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9348e007258667e1a650c97377d85d5f9356873adea7dcaad0b53888d837e971
- Size of remote file:
- 5.11 kB
- SHA256:
- 4d9387a08c40ab2221a567520f6f2ab33976a32ed8307ecfa0f1aa4a5df67200
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