Instructions to use zayn1111/deberta-v3-dnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zayn1111/deberta-v3-dnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zayn1111/deberta-v3-dnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zayn1111/deberta-v3-dnli") model = AutoModelForSequenceClassification.from_pretrained("zayn1111/deberta-v3-dnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac8995344149ff9e6f5150270ef9ad34d38affe29a901ced522a6f181b20c989
- Size of remote file:
- 4.92 kB
- SHA256:
- c88a760b3d67bd130291b0f2977f142285e096b9d190e620ad4933273032a900
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.