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:
- 3e7fc9fce43517bc2cc6635008e1550d39f4c350cd63c1093506d0f9369ca645
- Size of remote file:
- 3.42 MB
- SHA256:
- ed91415b8f4e15a5e2edebd1e96adc8686cda65e29df7a6c7f7dd539d0e3453b
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