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:
- c971d97a3fbd1686324d59dfe531feba554489a2d0faa56e5cf90c6a5d6ff036
- Size of remote file:
- 1.06 kB
- SHA256:
- 82c67f4c0c84490d9ab91ce25949988532c8a1049298729caa9fba405b74ea36
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