Instructions to use voidism/diffcse-bert-base-uncased-sts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidism/diffcse-bert-base-uncased-sts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="voidism/diffcse-bert-base-uncased-sts")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("voidism/diffcse-bert-base-uncased-sts") model = AutoModel.from_pretrained("voidism/diffcse-bert-base-uncased-sts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3a6c0347c7c28ba567e19561cbb2ba949d5813e5b8a885839103aea11636549
- Size of remote file:
- 1.25 GB
- SHA256:
- 39f53fc7e1db892f6a68aea4d1566c0e09a93bfaaa501380a528ad418d7e2a8c
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