Instructions to use bobox/DeBERTaV3-small-GeneralSentenceTransformer-checkpoints-tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bobox/DeBERTaV3-small-GeneralSentenceTransformer-checkpoints-tmp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bobox/DeBERTaV3-small-GeneralSentenceTransformer-checkpoints-tmp")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("bobox/DeBERTaV3-small-GeneralSentenceTransformer-checkpoints-tmp") model = AutoModel.from_pretrained("bobox/DeBERTaV3-small-GeneralSentenceTransformer-checkpoints-tmp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f7f3b79ea3b5e7b7388139f6e1f551f4ce60f2abc4b94abe971e3d179b6dcc3
- Size of remote file:
- 565 MB
- SHA256:
- e6b8f13689928c18ece3856866a5eabeea8661d8106e9cb8141da0943dbf28da
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