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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 241745fe32f9888dc193e843ea70643f378c01737b56fed951f70a2e81ca3c06
- Size of remote file:
- 5.05 kB
- SHA256:
- fb0bd895b3cb35ae663511b545c6c33197aed3cbbdf468d9f21ce4fc75a8ec8f
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