Instructions to use approach0/dpr-vanilla-bert-220 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use approach0/dpr-vanilla-bert-220 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="approach0/dpr-vanilla-bert-220")# Load model directly from transformers import AutoTokenizer, DprEncoder tokenizer = AutoTokenizer.from_pretrained("approach0/dpr-vanilla-bert-220") model = DprEncoder.from_pretrained("approach0/dpr-vanilla-bert-220") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ece612fbe9e868f88f3f17152f8254887836e8a4e783d44b012573936e8be381
- Size of remote file:
- 441 MB
- SHA256:
- fcbda85fdf16d41bf0dc58be3844f3580388ed92b79d7906a46f67646515e472
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