Instructions to use marcsun13/test_push_checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcsun13/test_push_checkpoint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="marcsun13/test_push_checkpoint")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("marcsun13/test_push_checkpoint") model = AutoModelForMaskedLM.from_pretrained("marcsun13/test_push_checkpoint") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd327ff2535b15fce175e747340204935973244c5ceac7b49ad0a707927caada
- Size of remote file:
- 5.05 kB
- SHA256:
- 64f4cae09864c3573f385ef38da1cad734cc9aba205b2a956790451c67e5ba42
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