Instructions to use mlx-community/Ling-2.6-flash-mlx-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Ling-2.6-flash-mlx-6bit 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/Ling-2.6-flash-mlx-6bit") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- MLX LM
How to use mlx-community/Ling-2.6-flash-mlx-6bit 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/Ling-2.6-flash-mlx-6bit" --prompt "Once upon a time"
- Xet hash:
- 70531859e3fa914b2296590b50fa69d47ccf692d99411a75acab6b809e5613f1
- Size of remote file:
- 12.2 MB
- SHA256:
- 1ce9d2d10f1d6da7b2439bc9655e51a00a8c5970f7dd015ae8407ca3962199f4
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