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:
- d63e70414b6dd51793f0e0b0e6431c642d134b071effa0bf2169c3374d8e0392
- Size of remote file:
- 867 MB
- SHA256:
- 32164ddf099914872bf9954388435c1fd839ba886e8ea3c56047562c998d5e73
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.