Instructions to use EndLessTime/fine_tuned_hswag_callback10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EndLessTime/fine_tuned_hswag_callback10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EndLessTime/fine_tuned_hswag_callback10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EndLessTime/fine_tuned_hswag_callback10") model = AutoModelForSequenceClassification.from_pretrained("EndLessTime/fine_tuned_hswag_callback10") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d84123cc9eb5098e3d9342e77a15fbd341f32d1c52f8abe36a83577664938c9
- Size of remote file:
- 5 GB
- SHA256:
- 0d002c2e9e4b776a76de2d3c944822257220e2804692485898094fcdc80b1fb9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.