Instructions to use Fabchi/Model_Mask_for_Wayne with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fabchi/Model_Mask_for_Wayne with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Fabchi/Model_Mask_for_Wayne")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Fabchi/Model_Mask_for_Wayne") model = AutoModelForMaskedLM.from_pretrained("Fabchi/Model_Mask_for_Wayne") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e664f79e901a6739a7b3065d67203dcb8c2400a920a19f1c35da603f1ad23b3f
- Size of remote file:
- 329 MB
- SHA256:
- c8fa305b0276e65b73467bbe340cb85b90bfb731d12b873eb74cb783de99e86f
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