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:
- dc910aa02ec38370f9afec743afa0c499bb1ff871d46375db9284c5e3f29ad05
- Size of remote file:
- 407 MB
- SHA256:
- b129d0ae906c9579f8d118d9a84df27304676d6e8822389c776e8ea33423feb5
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