Instructions to use lukecarlate/Yang_CM_Num with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/Yang_CM_Num with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/Yang_CM_Num")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/Yang_CM_Num") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/Yang_CM_Num") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d454a8f8b91fc32bd85c83327b3c85c8982266a46709eb15888cef35ee31ff8e
- Size of remote file:
- 439 MB
- SHA256:
- 9a415fbe29f7d2d93a7ca4dd0b936586ed3198aa4cea0ae79a41bcb57a3e1a06
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