# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("DataHammer/mozi_llama_7b", device_map="auto")Quick Links
Model Details
Model Description
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]
- Repository: Github Repo
- Paper [optional]: Paper Repo
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="DataHammer/mozi_llama_7b")