Instructions to use approach0/dpr-cotbert-020 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use approach0/dpr-cotbert-020 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="approach0/dpr-cotbert-020")# Load model directly from transformers import AutoTokenizer, DprEncoder tokenizer = AutoTokenizer.from_pretrained("approach0/dpr-cotbert-020") model = DprEncoder.from_pretrained("approach0/dpr-cotbert-020", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 593ce4a44e541b2f18ef95517f7ba7b92ae79f8ac09ca2e652376d7f9b98d25c
- Size of remote file:
- 441 MB
- SHA256:
- ff6b5a493d791892bad725707e475b75a49ac56826b9c86febcb3db02a0b0616
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