Instructions to use fanjiang98/ABEL-Query-Encoder-Warmup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fanjiang98/ABEL-Query-Encoder-Warmup with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fanjiang98/ABEL-Query-Encoder-Warmup")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fanjiang98/ABEL-Query-Encoder-Warmup") model = AutoModel.from_pretrained("fanjiang98/ABEL-Query-Encoder-Warmup") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd0d120f9182f2b0a37a1c0624cf6e16c67828b1b5f9eb08892b931c66ad2d3d
- Size of remote file:
- 438 MB
- SHA256:
- a728e624ccc84bee421f04e9d66cbc10244d9c4b63b7f33e54046958a8f92a6d
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