Instructions to use adasgaleus/insertion-prop05-ls01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adasgaleus/insertion-prop05-ls01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="adasgaleus/insertion-prop05-ls01")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("adasgaleus/insertion-prop05-ls01") model = AutoModelForTokenClassification.from_pretrained("adasgaleus/insertion-prop05-ls01") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b9c8a36d9b0f1e48c5f98ca5de828228ee034aa8930b6b042384fd364c35bcf
- Size of remote file:
- 265 MB
- SHA256:
- e2d09425a7a86ec3d1fa131f0b70bdc0f95a4ab04c0df97c8d3bc5bb3d017888
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