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license: apache-2.0 |
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datasets: |
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- allenai/qasper |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: sentence-similarity |
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--- |
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# SciDPR Context Encoder |
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<!-- Provide a quick summary of what the model is/does. --> |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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Dense Passage Retrieval (DPR) is a set of tools and models for state-of-the-art open-domain Q&A research. scidpr-ctx-encoder is the Context Encoder trained using the Scientific Question Answer (QA) dataset (Pradeep et al., 2021). |
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- **Developed by:** See [GitHub repo](https://github.com/gmftbyGMFTBY/science-llm) for model developers |
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- **Model type:** BERT-based encoder |
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- **Language(s) (NLP):** [Apache 2.0](https://github.com/gmftbyGMFTBY/science-llm/blob/main/LICENSE) |
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- **License:** English |
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### Model Sources [optional] |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** [Github Repo](https://github.com/gmftbyGMFTBY/science-llm) |
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- **Paper [optional]:** [Paper Repo]() |
