Instructions to use adasgaleus/insertion-prop-05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adasgaleus/insertion-prop-05 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="adasgaleus/insertion-prop-05")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("adasgaleus/insertion-prop-05") model = AutoModelForTokenClassification.from_pretrained("adasgaleus/insertion-prop-05") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0e55a9ecb41f10e83f2ca88647d24936bccd4b5acac417995425feb6427d49a
- Size of remote file:
- 265 MB
- SHA256:
- 883f681f7788e35cf01d550d1178aaf311cddf7545e415005356bfc5cd8e4215
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