Instructions to use mlx-community/YandexGPTQ6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/YandexGPTQ6 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/YandexGPTQ6") 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/YandexGPTQ6 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/YandexGPTQ6" --prompt "Once upon a time"
- Xet hash:
- c36b94f5e4cb02b88d73b83d6d46c7b9e6196e2802c86249f3b0f4ae4e3d363f
- Size of remote file:
- 2.57 MB
- SHA256:
- 1676f5bfc73d8a14b51da588b815b7c0158a0e33db9522ea1d409720bcc7dca1
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