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:
- 5a5e1bdd7abc8de62a5b3deed38fe8637ae7e3c149e7a89afc3f6eec5481f200
- Size of remote file:
- 3.45 kB
- SHA256:
- 7ddb9574d7dcb3e3b3689b32f0ded008c13db2759e1b43fd19dfd34d63037d44
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