Downloads · 30 days
11
7% of all-time downloads
Gemma-4-E4B-dailydialog-MLX-4bit
supersamdev/Gemma-4-E4B-dailydialog-MLX-4bit
Gemma-4-E4B-dailydialog-MLX-4bit is a machine learning model from supersamdev. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as gemma.
4bit MLX quantization of supersamdev/Gemma-4-E4B-dailydialog-16bit, a Gemma 4 4B VLM fine-tuned on DailyDialog.
All-time downloads
160
Public
Parameters
8B
6.9 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors6.8 GB · 100%
Parameter types
How the weights are stored.
U327.5B · 94%
Base models
Model card
From the Hugging Face model README
Gemma-4-E4B-dailydialog MLX 4bit
4bit MLX quantization of supersamdev/Gemma-4-E4B-dailydialog-16bit, a Gemma 4 4B VLM fine-tuned on DailyDialog.
Requires Apple Silicon (M1/M2/M3/M4). RAM needed: ~6 GB.
Usage
pip install mlx-vlm
from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config
model_path = "supersamdev/Gemma-4-E4B-dailydialog-MLX-4bit"
model, processor = load(model_path)
config = load_config(model_path)
prompt = apply_chat_template(processor, config, "Hello!", num_images=0)
response = generate(model, processor, prompt, max_tokens=200, verbose=True)
Other Quants
| Repo | Bits | RAM |
|---|---|---|
| Gemma-4-E4B-dailydialog-MLX-2bit | 2-bit | ~3 GB |
| Gemma-4-E4B-dailydialog-MLX-4bit | 4-bit | ~6 GB |
| Gemma-4-E4B-dailydialog-MLX-6bit | 6-bit | ~8 GB |
| Gemma-4-E4B-dailydialog-MLX-8bit | 8-bit | ~10 GB |
Parent Model
supersamdev/Gemma-4-E4B-dailydialog-16bit
Quantization
Converted using mlx-vlm on Apple Silicon.
- Library
- mlx
- Type
- gemma4
- License
- gemma
- Languages
- en
- Created
- May 18, 2026
- Updated
- May 18, 2026