Instructions to use augustinLib/test_upload with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use augustinLib/test_upload with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="augustinLib/test_upload")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("augustinLib/test_upload") model = AutoModelForSequenceClassification.from_pretrained("augustinLib/test_upload") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a4a816c1ccb108739cafcf3870d336624540a9f2c27594cab1b377096a6b619
- Size of remote file:
- 4.6 kB
- SHA256:
- ef497d325afe3e86cca7612327ec0dcd8645561a95165a813e44423dd8f8939d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.