Instructions to use dsksd/dpr-question_encoder-single-qrecc-model-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsksd/dpr-question_encoder-single-qrecc-model-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dsksd/dpr-question_encoder-single-qrecc-model-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dsksd/dpr-question_encoder-single-qrecc-model-base") model = AutoModel.from_pretrained("dsksd/dpr-question_encoder-single-qrecc-model-base") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:8e26a1c4d5811b46763dadb707bd022708e06109166837aec8f19b55efedd66c
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size 437961112
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