Instructions to use NexVeridian/gemma-4-E4B-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use NexVeridian/gemma-4-E4B-8bit 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-8bit") 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-8bit 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-8bit" --prompt "Once upon a time"
ValueError: Received 126 parameters not in model.
#1
by p215636 - opened
I’m trying to run the model NexVeridian/gemma-4-E4B-8bit as the model card suggests and I’m getting a ValueError: Received 126 parameters not in model
My MLX version is 0.31.2 and MLX-LM is 0.31.3
I resort to pip install --upgrade --no-cache-dir mlx-lm mlx in the hope that this would clean the slate and resolve any conflicts, but regrettable no success. Can you kindly confirm if it still works on your setup or provide some suggestions as to what I’m missing…
Thanking you in advance…