MLX How to use GazTrab/Gemma3-CLIP-1b-it-qat-MLX 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("GazTrab/Gemma3-CLIP-1b-it-qat-MLX")
prompt = "Once upon a time in"
text = generate(model, tokenizer, prompt=prompt, verbose=True) Unsloth Studio How to use GazTrab/Gemma3-CLIP-1b-it-qat-MLX with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for GazTrab/Gemma3-CLIP-1b-it-qat-MLX to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for GazTrab/Gemma3-CLIP-1b-it-qat-MLX to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for GazTrab/Gemma3-CLIP-1b-it-qat-MLX to start chatting
Load model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="GazTrab/Gemma3-CLIP-1b-it-qat-MLX",
max_seq_length=2048,
) 
