Instructions to use sapbot/gemma-3n-4b-it-distill-smollm2-360m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sapbot/gemma-3n-4b-it-distill-smollm2-360m with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-360M-Instruct")
model = PeftModel.from_pretrained(base_model, "sapbot/gemma-3n-4b-it-distill-smollm2-360m")

Transformers

How to use sapbot/gemma-3n-4b-it-distill-smollm2-360m with Transformers:

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

pipe = pipeline("text-generation", model="sapbot/gemma-3n-4b-it-distill-smollm2-360m")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("sapbot/gemma-3n-4b-it-distill-smollm2-360m", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use sapbot/gemma-3n-4b-it-distill-smollm2-360m with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sapbot/gemma-3n-4b-it-distill-smollm2-360m"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sapbot/gemma-3n-4b-it-distill-smollm2-360m",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/sapbot/gemma-3n-4b-it-distill-smollm2-360m

SGLang

How to use sapbot/gemma-3n-4b-it-distill-smollm2-360m 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 "sapbot/gemma-3n-4b-it-distill-smollm2-360m" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sapbot/gemma-3n-4b-it-distill-smollm2-360m",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "sapbot/gemma-3n-4b-it-distill-smollm2-360m" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sapbot/gemma-3n-4b-it-distill-smollm2-360m",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use sapbot/gemma-3n-4b-it-distill-smollm2-360m with Docker Model Runner:
```
docker model run hf.co/sapbot/gemma-3n-4b-it-distill-smollm2-360m
```

sapbot commited on May 8

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@@ -20,6 +20,9 @@ language:
 # Gemma 3n 4B Distill SmolLM2 360M Instruct
 This model is a fine-tuned version of [unsloth/SmolLM2-360M-Instruct](https://huggingface.co/unsloth/SmolLM2-360M-Instruct) on the [sapbot/gemma-3n-4b-it-423x](https://huggingface.co/datasets/sapbot/gemma-3n-4b-it-423x) dataset.
 ## Model description

 # Gemma 3n 4B Distill SmolLM2 360M Instruct
+**WARNING:** REMEMBER TO ADD CUSTOM SYSTEM PROMPT RESEMBLING GEMMA 3N 4B IF YOU WANT MODEL TO KNOW THAT IT'S IT, BECAUSE THE ONLY THING CHANGED IS STYLE, IN DATASET THERE WERE NO SIGNS
+OF TEACHER MODEL. HAVE FUN.
 This model is a fine-tuned version of [unsloth/SmolLM2-360M-Instruct](https://huggingface.co/unsloth/SmolLM2-360M-Instruct) on the [sapbot/gemma-3n-4b-it-423x](https://huggingface.co/datasets/sapbot/gemma-3n-4b-it-423x) dataset.
 ## Model description