Instructions to use nadellaroshni/test_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nadellaroshni/test_model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nadellaroshni/test_model2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nadellaroshni/test_model2") model = AutoModelForSequenceClassification.from_pretrained("nadellaroshni/test_model2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a743a9960e301b6715a5a19b83bf85311352229e46abf066d8bab4df1e93eddc
- Size of remote file:
- 4.66 kB
- SHA256:
- 6f3973722fece9334c17c2dd4b5240e0d0a11a2d942e44af54469dc4b47fb231
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.