Instructions to use potsawee/deberta-v3-large-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use potsawee/deberta-v3-large-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="potsawee/deberta-v3-large-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("potsawee/deberta-v3-large-mnli") model = AutoModelForSequenceClassification.from_pretrained("potsawee/deberta-v3-large-mnli", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e34895255013ac0bfb9a2369faf5708d4748f30de4256d6dc34c9faa9163b0e2
- Size of remote file:
- 1.74 GB
- SHA256:
- 636786a52933012ff449548115da19faca47f2643ef3684acc3cc77f545a5cb6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.