Instructions to use mlx-community/codegemma-1.1-2b-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mlx-community/codegemma-1.1-2b-4bit with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="mlx-community/codegemma-1.1-2b-4bit")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mlx-community/codegemma-1.1-2b-4bit")
model = AutoModelForCausalLM.from_pretrained("mlx-community/codegemma-1.1-2b-4bit")

MLX

How to use mlx-community/codegemma-1.1-2b-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("mlx-community/codegemma-1.1-2b-4bit")

prompt = "Once upon a time in"
text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

vLLM

How to use mlx-community/codegemma-1.1-2b-4bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mlx-community/codegemma-1.1-2b-4bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlx-community/codegemma-1.1-2b-4bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mlx-community/codegemma-1.1-2b-4bit

SGLang

How to use mlx-community/codegemma-1.1-2b-4bit with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "mlx-community/codegemma-1.1-2b-4bit" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlx-community/codegemma-1.1-2b-4bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "mlx-community/codegemma-1.1-2b-4bit" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlx-community/codegemma-1.1-2b-4bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

MLX LM

How to use mlx-community/codegemma-1.1-2b-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 "mlx-community/codegemma-1.1-2b-4bit" --prompt "Once upon a time"

Docker Model Runner
How to use mlx-community/codegemma-1.1-2b-4bit with Docker Model Runner:
```
docker model run hf.co/mlx-community/codegemma-1.1-2b-4bit
```

Update README.md

by olegshulyakov - opened May 30, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-4

Files changed (1) hide show

README.md +7 -4

README.md CHANGED Viewed

@@ -4,11 +4,14 @@ library_name: transformers
 tags:
 - mlx
 extra_gated_heading: Access CodeGemma on Hugging Face
-extra_gated_prompt: To access CodeGemma on Hugging Face, you’re required to review
-  and agree to Google’s usage license. To do this, please ensure you’re logged-in
-  to Hugging Face and click below. Requests are processed immediately.
 extra_gated_button_content: Acknowledge license
 license_link: https://ai.google.dev/gemma/terms
 ---
 # mlx-community/codegemma-1.1-2b-4bit
@@ -25,4 +28,4 @@ from mlx_lm import load, generate
 model, tokenizer = load("mlx-community/codegemma-1.1-2b-4bit")
 response = generate(model, tokenizer, prompt="hello", verbose=True)
-```

 tags:
 - mlx
 extra_gated_heading: Access CodeGemma on Hugging Face
+extra_gated_prompt: >-
+  To access CodeGemma on Hugging Face, you’re required to review and agree to
+  Google’s usage license. To do this, please ensure you’re logged-in to Hugging
+  Face and click below. Requests are processed immediately.
 extra_gated_button_content: Acknowledge license
 license_link: https://ai.google.dev/gemma/terms
+base_model:
+- google/codegemma-1.1-2b
 ---
 # mlx-community/codegemma-1.1-2b-4bit
 model, tokenizer = load("mlx-community/codegemma-1.1-2b-4bit")
 response = generate(model, tokenizer, prompt="hello", verbose=True)
+```