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:
- aa7877ceeed8ec012caf670263c6a6602c5b11099788a243b600bc8e453d2f03
- Size of remote file:
- 3 kB
- SHA256:
- 6e7de478fe56bb314a04cff488eff9d7a9672f7a1c12803df279ba533bc4b7d0
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