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---
license: apache-2.0
language:
- en
---
## Information
This is a Exl2 quantized version of [Buttercup-4x7B-bf16](https://huggingface.co/Kquant03/Buttercup-4x7B-bf16)
Please refer to the original creator for more information.
Calibration dataset: Exllamav2 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).
- Please ask for more bpws in the community tab if necessary.
## 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)
If you don't have huggingface-cli, please run `pip install huggingface_hub`.
To run this model, follow these steps:
1. Make a directory inside your models folder called `Buttercup-4x7B-bf16-exl2`
2. Open a terminal inside your models folder
3. Run `huggingface-cli download royallab/Buttercup-4x7B-bf16-exl2 --revision 6.0bpw-h6 --local-dir Buttercup-4x7B-bf16-exl2 --local-dir-use-symlinks False`
1. The `--revision` flag corresponds to the branch name on the model repo. Please select the appropriate bpw branch for your system.
4. Inside TabbyAPI's config.yml, set `model_name` to `Buttercup-4x7B-bf16-exl2` or you can use the `/model/load` endpoint after launching.
5. Launch TabbyAPI inside your python env by running `python main.py`
## 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/doctorshotgun
You should not feel obligated to donate, but if you do, I'd appreciate it.
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