Instructions to use approach0/dpr-cotbert-220 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use approach0/dpr-cotbert-220 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="approach0/dpr-cotbert-220")# Load model directly from transformers import AutoTokenizer, DprEncoder tokenizer = AutoTokenizer.from_pretrained("approach0/dpr-cotbert-220") model = DprEncoder.from_pretrained("approach0/dpr-cotbert-220") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad6238f856588a27f46ec87dc3dc2705d3f285e73d9e4bf714536bb3dc03b1ac
- Size of remote file:
- 441 MB
- SHA256:
- cc578a17ef5972343367fb151779a2df055881e6beae61f7d8c9371ffbf858dd
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