Instructions to use explosion-testing/deberta-v3-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use explosion-testing/deberta-v3-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="explosion-testing/deberta-v3-test")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("explosion-testing/deberta-v3-test") model = AutoModel.from_pretrained("explosion-testing/deberta-v3-test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5c73416d0f2c3501579d3839623eff8569d3ca2cc4c5073a71c4e6142c68ad3
- Size of remote file:
- 416 kB
- SHA256:
- 6e13c98d18b846ac0c672b2c317476a88ef49d1b158d1c45bc7e47f5bb0cf5a2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.