Instructions to use canIjoin/datafun with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use canIjoin/datafun with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="canIjoin/datafun")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("canIjoin/datafun") model = AutoModelForTokenClassification.from_pretrained("canIjoin/datafun", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 094d8a5f6622d1360a55c455441bf06dc83547b9cc9af1749d9f22aae97185aa
- Size of remote file:
- 407 MB
- SHA256:
- 0902a7ced1d20dd65a1862f8cd03484495a6b322e59c1d0e294dc66c67723177
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