Instructions to use lukecarlate/Yang_Num with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/Yang_Num with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/Yang_Num")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/Yang_Num") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/Yang_Num") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e691e2517be26f32e4c8626e7fe975819e8d2d5f0a19a21bc5ee68b7f1e7c01e
- Size of remote file:
- 439 MB
- SHA256:
- 7fce94aaa6e7a7adb9bbab4af34e3c99a59f6876c13dfba03fd021b645f59d47
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