Instructions to use mlx-community/Yi-9B-q with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Yi-9B-q with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/Yi-9B-q") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use mlx-community/Yi-9B-q with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "mlx-community/Yi-9B-q" --prompt "Once upon a time"
Update README.md with license information
Hi, I'm Chen, a DevRel specialist from 01.AI.
Today I'm sending you the PR to help you update the model license, and give a recommendation according to apache-2.0.
License Update:
Since license of all Yi Series models has been updated from yi-license to apache-2.0, this PR is to help you update it.
License under apache-2.0 enables more free and flexible use and distribution, promoting open collaboration and innovation.
It can be a good choice to make your models widely available and provide access which is reliable and high-quality. (https://www.apache.org/licenses/LICENSE-2.0)
If it looks good to you, you can choose to update other yi derivatives (if you have) license to apache-2.0 on your own if I miss out.
Recommendation for Yi Derivatives:
All Yi Series models are now licensed under apache-2.0. It is recomended that Yi derivatives mention the specific Yi models they're based on in any place (e.g., in the Model Card) to align with the requirement of apache-2.0.
Thanks for your continued support and contributions to Yi models.
Hi, have you reviewed this PR? If it looks good to you, you can merge it! 😀