Instructions to use fanjiang98/ABEL-Query-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fanjiang98/ABEL-Query-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fanjiang98/ABEL-Query-Encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fanjiang98/ABEL-Query-Encoder") model = AutoModel.from_pretrained("fanjiang98/ABEL-Query-Encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 362ca22eca1205641aa724b33ce6904983aec7cb980025f5f9fd36682db5a4f6
- Size of remote file:
- 438 MB
- SHA256:
- 6042f1b4836f52fe10c4e78486a20aca6ffc6109bcb672946f58c318a199e0e4
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