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---
language:
- en
---
## Information
This is a Exl2 quantized version of [MN-12B-Starsong-v1](https://huggingface.co/aetherwiing/MN-12B-Starsong-v1)
Please refer to the original creator for more information.
Calibration dataset: Exl2 default
## Branches:
- main: Measurement files
- 4bpw: 4 bits per weight
- 5bpw: 5 bits per weight
- 6bpw: 6 bits per weight
## Notes
- 6bpw is recommended for the best quality to vram usage ratio (assuming you have enough vram).
- Quants greater than 6bpw will not be created because there is no improvement in using them. If you really want them, ask someone else or make them yourself.
## Download
With [async-hf-downloader](https://github.com/theroyallab/async-hf-downloader): A lightweight and asynchronous huggingface downloader created by me
```shell
./async-hf-downloader royallab/MN-12B-Starsong-v1-exl2 -r 6bpw -p MN-12B-Starsong-v1-exl2-6bpw
```
With HuggingFace hub (`pip install huggingface_hub`)
```shell
huggingface-cli download royallab/MN-12B-Starsong-v1-exl2 --revision 6bpw --local-dir MN-12B-Starsong-v1-exl2-6bpw
```
## Run in TabbyAPI
TabbyAPI is a pure exllamav2 FastAPI server developed by us. You can find TabbyAPI's source code here: [https://github.com/theroyallab/TabbyAPI](https://github.com/theroyallab/TabbyAPI)
1. Inside TabbyAPI's config.yml, set `model_name` to `MN-12B-Starsong-v1-exl2-6bpw`
1. You can also use an argument `--model_name MN-12B-Starsong-v1-exl2-6bpw` on startup or you can use the `/v1/model/load` endpoint
2. Launch TabbyAPI inside your python env by running `./start.bat` or `./start.sh`
## Donate?
All my infrastructure and cloud expenses are paid out of pocket. If you'd like to donate, you can do so here: https://ko-fi.com/kingbri
You should not feel obligated to donate, but if you do, I'd appreciate it.
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