Downloads · 30 days
0
0% of all-time downloads
royallab/Kimiko-10.7B-v3-exl2
Kimiko-10.7B-v3-exl2 is a machine learning model from royallab. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This is a Exl2 quantized version of Kimiko-10.7B-v3
Downloads · 30 days
0
0% of all-time downloads
All-time downloads
2
Public
Repo size
20.8 GB
Likes
0
Public
Click a slice to open those files.
.json2.7 MB · 100%
From the Hugging Face model README
This is a Exl2 quantized version of Kimiko-10.7B-v3
Please refer to the original creator for more information.
Calibration dataset: Exllamav2 default
TabbyAPI is a pure exllamav2 FastAPI server developed by us. You can find TabbyAPI's source code here: 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:
Make a directory inside your models folder called Kimiko-10.7B-v3-exl2
Open a terminal inside your models folder
Run huggingface-cli download royallab/Kimiko-10.7B-v3-exl2 --revision 4bpw --local-dir Kimiko-10.7B-v3-exl2 --local-dir-use-symlinks False
--revision flag corresponds to the branch name on the model repo. Please select the appropriate bpw branch for your system.Inside TabbyAPI's config.yml, set model_name to Kimiko-10.7B-v3-exl2 or you can use the /model/load endpoint after launching.
Launch TabbyAPI inside your python env by running python main.py
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