Instructions to use facebook/dragon-plus-context-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dragon-plus-context-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/dragon-plus-context-encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("facebook/dragon-plus-context-encoder") model = AutoModelForMaskedLM.from_pretrained("facebook/dragon-plus-context-encoder", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef319c00312d279d49ebcd878853acd70d0207322e0f508a433f30bd1220460d
- Size of remote file:
- 438 MB
- SHA256:
- 5133b88ee2299201ee669efc57dbce12b52542684708bbc0529c8e9dfec02462
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