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:
- 27a9c350d370cbe8f5ca3712b1213745baf0ca2bed5d65e1982df9fd56591e3c
- Size of remote file:
- 867 MB
- SHA256:
- 2718ff8526278b7841fa6f6f93b7478030381c430ffb91ae1df75b12527d1395
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