Instructions to use facebook/dragon-roberta-query-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dragon-roberta-query-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/dragon-roberta-query-encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("facebook/dragon-roberta-query-encoder") model = AutoModelForMaskedLM.from_pretrained("facebook/dragon-roberta-query-encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7078e092ac59942e4f758bdc24b4d898ecaf05039d23f4d14eacae11e622e86f
- Size of remote file:
- 499 MB
- SHA256:
- 05670fab6852730bdfdf0f810fe2abfa5bc8dacfe54bf8f57990dfa24bfc82e2
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