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:
- e0987ae4d62a7a72d9cc33b4ca77c1c3111ad67a6b2fcb16e49c85b86db8c072
- Size of remote file:
- 5.62 kB
- SHA256:
- 3b7d09e178b7126106b67daae47202be477d3e950354366f995c79aad0ae7f8f
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