Instructions to use voidful/dpr-ctx_encoder-bert-base-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/dpr-ctx_encoder-bert-base-multilingual with Transformers:
# Load model directly from transformers import AutoTokenizer, DPRContextEncoder tokenizer = AutoTokenizer.from_pretrained("voidful/dpr-ctx_encoder-bert-base-multilingual") model = DPRContextEncoder.from_pretrained("voidful/dpr-ctx_encoder-bert-base-multilingual") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 339352f0b023a44d604eb5972d80b3f94bee606c14f8f671e3b85db586a82dcc
- Size of remote file:
- 712 MB
- SHA256:
- 76d3253834b15aa69beebbada742b8decd39c5a59b4acb23781fc58ba06cefc0
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