Instructions to use adasgaleus/insertbert05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adasgaleus/insertbert05 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="adasgaleus/insertbert05")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("adasgaleus/insertbert05") model = AutoModelForTokenClassification.from_pretrained("adasgaleus/insertbert05") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23401835d385c9df2953b72b2610ea4b71f50f5aad0a1a4d416d462aa50ad282
- Size of remote file:
- 265 MB
- SHA256:
- 731ff1f1fa9204b9e505fc4a48e2ba20221a3b501290956d363c7b9bce589395
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