Instructions to use avacaondata/dpr-query-uned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avacaondata/dpr-query-uned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="avacaondata/dpr-query-uned")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("avacaondata/dpr-query-uned") model = AutoModelForMaskedLM.from_pretrained("avacaondata/dpr-query-uned") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2ecb984afb9c30064c29494f5b9445d7533344543827a95ec3cb274540d6462
- Size of remote file:
- 439 MB
- SHA256:
- ebc6ff49d87fb22e01d03520d5bde61f92aacd2cdf8c3c9b34de6b925d6bd96b
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