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:
- 8d0057e6000c157e3f41a8c4cac4c0535bec85a32896753289231de4afb5cb69
- Size of remote file:
- 867 MB
- SHA256:
- aa9740f7ef34783948b62437f5e00eef71668e1b0ed1fc9d910880e8183a3067
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