Instructions to use CS1995/initial-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CS1995/initial-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CS1995/initial-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CS1995/initial-test") model = AutoModelForSequenceClassification.from_pretrained("CS1995/initial-test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6490609c84b175564cf9acbc36e9c4c00a558c064db07e7d92aa088da72e9c84
- Size of remote file:
- 4.92 kB
- SHA256:
- 9cf8f427cf49298513a7114d5b3b21d0a10a7ab20fae9a67e21b2602b25587e2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.