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
- 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:
- d801d5d51a7154272c47652aa97b6071e7bef26cbf36dac7ca85496304dc30d6
- Size of remote file:
- 17.5 MB
- SHA256:
- d0d908b4f9326e0998815690e325b6abbd378978553e10627924dd825db7e243
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