Instructions to use NexVeridian/gemma-4-E4B-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use NexVeridian/gemma-4-E4B-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("NexVeridian/gemma-4-E4B-6bit") 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 NexVeridian/gemma-4-E4B-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 "NexVeridian/gemma-4-E4B-6bit" --prompt "Once upon a time"
- Xet hash:
- 11a39e16eab4341183970285f0237d608ef9c2ee0c00b0b4fe7636545dcfe04d
- Size of remote file:
- 3.75 GB
- SHA256:
- 55ae5326e43f917cf839dfdd4f9790dd24a992a8e70353a3707916cb7f8e4d21
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