Instructions to use facebook/dragon-plus-query-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dragon-plus-query-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/dragon-plus-query-encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("facebook/dragon-plus-query-encoder") model = AutoModelForMaskedLM.from_pretrained("facebook/dragon-plus-query-encoder") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbc1cf42c9830d73adcd950f723456f79f527bfd729e3cbcff7ee0a4051b9acd
- Size of remote file:
- 438 MB
- SHA256:
- c6eb0b85010b03dd634fa2a035591f3d8c5bc6ac1188c50a7e3f811526d995f7
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