Instructions to use mlx-community/gemma-2b-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/gemma-2b-coder 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/gemma-2b-coder") 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/gemma-2b-coder 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/gemma-2b-coder" --prompt "Once upon a time"
- Xet hash:
- 0eaaacac15668c43fce4a8632fde98375b76196743c777d1c98052826e652d31
- Size of remote file:
- 4.24 MB
- SHA256:
- 6969e64047744a44bb3abfb5c50f8de0f7ed8b571d5444426ef931f651d1a0ef
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