---
language:
- en
library_name: transformers
pipeline_tag: question-answering
license: apache-2.0
datasets:
- togethercomputer/RedPajama-Data-1T
- allenai/qasper
- DataHammer/paper_ground_dialog
metrics:
- bleu
- rouge
- f1
- bertscore
---

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->
Dense Passage Retrieval (DPR) is a set of tools and models for state-of-the-art open-domain Q&A research. scidpr-question-encoder is the Question Encoder trained using the Scientific Question Answer (QA) dataset (Pradeep et al., 2021).


- **Developed by:** See [GitHub repo](https://github.com/gmftbyGMFTBY/science-llm) for model developers
- **Model date:** LLaMA was trained In May. 2023.
- **Model version:** This is version 1 of the model.
- **Model type:** mozi_llama is an auto-regressive language model, based on the transformer architecture. The model comes in different sizes: 7B parameters.
- **Language(s) (NLP):** [Apache 2.0](https://github.com/gmftbyGMFTBY/science-llm/blob/main/LICENSE)
- **License:** English

### Model Sources [optional]

<!-- Provide the basic links for the model. -->

- **Repository:** [Girhub Repo](https://github.com/gmftbyGMFTBY/science-llm)
- **Paper [optional]:** [Paper Repo]()