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Merge branch 'main' of github.com:Vision-CAIR/MiniGPT-4 into main

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#	README.md
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@ -3,7 +3,7 @@
**King Abdullah University of Science and Technology**
<a href='https://minigpt-4.github.io'><img src='https://img.shields.io/badge/Project-Page-Green'></a> <a href='MiniGPT_4.pdf'><img src='https://img.shields.io/badge/Paper-PDF-red'></a>
<a href='https://minigpt-4.github.io'><img src='https://img.shields.io/badge/Project-Page-Green'></a> <a href='MiniGPT_4.pdf'><img src='https://img.shields.io/badge/Paper-PDF-red'></a> <a href='https://huggingface.co/spaces/Vision-CAIR/minigpt4'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a> <a href='https://huggingface.co/Vision-CAIR/MiniGPT-4'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-blue'></a> [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/camenduru/MiniGPT-4-colab/blob/main/minigpt4_colab.ipynb) [![YouTube](https://badges.aleen42.com/src/youtube.svg)](https://www.youtube.com/watch?v=__tftoxpBAw&feature=youtu.be)
## Online Demo
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The current version of MiniGPT-4 is built on the v0 versoin of Vicuna-13B.
Please refer to our instruction [here](PrepareVicuna.md)
to prepare the Vicuna weights.
The final weights would be in a single folder with the following structure:
The final weights would be in a single folder in a structure similar to the following:
```
vicuna_weights
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To save GPU memory, Vicuna loads as 8 bit by default, with a beam search width of 1.
This configuration requires about 23G GPU memory for Vicuna 13B and 11.5G GPU memory for Vicuna 7B.
For more powerful GPUs, you can run the model
For more powerful GPUs, you can run the model
in 16 bit by setting low_resource to False in the config file
[minigpt4_eval.yaml](eval_configs/minigpt4_eval.yaml) and use a larger beam search width.
Thanks [@camenduru](https://github.com/camenduru), you can also run our code on [Colab](https://colab.research.google.com/github/camenduru/MiniGPT-4-colab/blob/main/minigpt4_colab.ipynb)
### Training
The training of MiniGPT-4 contains two alignment stages.