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mozi_llama_7b
DataHammer/mozi_llama_7b
mozi_llama_7b is a question answering model from DataHammer. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as apache-2.0.
Mozi is the first large-scale language model for the scientific paper domain, such as question answering and emotional support. With the help of the large-scale language and evidence retrieval models, SciDPR, Mozi gen…
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Public
Updated Jun 29, 2023
Repo size
320 MB
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2
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.bin320 MB · 100%
At a glance
- Task
- Question Answering
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Jun 28, 2023
- Updated
- Jun 29, 2023
- SHA
- 3dd961d0
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Model card
From the Hugging Face model README
Model Details
Model Description
<!-- Provide a longer summary of what this model is. -->Mozi is the first large-scale language model for the scientific paper domain, such as question answering and emotional support. With the help of the large-scale language and evidence retrieval models, SciDPR, Mozi generates concise and accurate responses to users' questions about specific papers and provides emotional support for academic researchers.
- Developed by: See GitHub repo for model developers
- Model date: Mozi was trained In May. 2023.
- Model version: This is version 1 of the model.
- Model type: Mozi 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
- License: English
Model Sources [optional]
<!-- Provide the basic links for the model. -->- Repository: Github Repo
- Paper [optional]: Paper Repo
- Task
- Question Answering
- Library
- transformers
- License
- apache-2.0
- Languages
- en
- Created
- Jun 28, 2023
- Updated
- Jun 29, 2023