Instructions to use vblagoje/dpr-question_encoder-single-lfqa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vblagoje/dpr-question_encoder-single-lfqa-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="vblagoje/dpr-question_encoder-single-lfqa-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("vblagoje/dpr-question_encoder-single-lfqa-base") model = AutoModel.from_pretrained("vblagoje/dpr-question_encoder-single-lfqa-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model
This is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.62ceb9a
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Update config.json
Use DPRQuestionEncoder architecturefd2656c
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Create README.md
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Update, Rprec:0.056, recall@5: 0.125
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No checkpoints, accuracy@1: 0.18, mrr: 0.32
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Update model, accuracy@1: 0.2, mrr: 0.33
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Update Accuracy@1: 0.19, mrr: 0.32
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Update, mrr@10 0.55
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Use projection_dim 128
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Initial version
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initial commit
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