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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf0cf274717829a65e81b488075ce52f8298747b4746215ef4d891a393eda3fa
- Size of remote file:
- 407 MB
- SHA256:
- b865252516115c46bc508167fa2258f198bcce520eb7a1ac4fbf8d50dc361368
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