Instructions to use Siarhei/gemma-4-E4B-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Siarhei/gemma-4-E4B-4bit 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("Siarhei/gemma-4-E4B-4bit") 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 Siarhei/gemma-4-E4B-4bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "Siarhei/gemma-4-E4B-4bit" --prompt "Once upon a time"
- Xet hash:
- 2e7ad99fe28ec40cd28867fbe6c65c1ec92ce18051c4fdb8eccad32e16989ada
- Size of remote file:
- 32.2 MB
- SHA256:
- 12bac982b793c44b03d52a250a9f0d0b666813da566b910c24a6da0695fd11e6
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