Instructions to use unsloth/gemma-3n-E2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/gemma-3n-E2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="unsloth/gemma-3n-E2B")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("unsloth/gemma-3n-E2B") model = AutoModelForMultimodalLM.from_pretrained("unsloth/gemma-3n-E2B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use unsloth/gemma-3n-E2B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "unsloth/gemma-3n-E2B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "unsloth/gemma-3n-E2B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/unsloth/gemma-3n-E2B
- SGLang
How to use unsloth/gemma-3n-E2B 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 "unsloth/gemma-3n-E2B" \ --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": "unsloth/gemma-3n-E2B", "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 "unsloth/gemma-3n-E2B" \ --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": "unsloth/gemma-3n-E2B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Desktop
- Docker Model Runner
How to use unsloth/gemma-3n-E2B with Docker Model Runner:
docker model run hf.co/unsloth/gemma-3n-E2B
Download tokenizer.model from unsloth/gemma-3n-E2B: direct link, hf CLI and curl.
- Browser
- Download file 4.7 MB
-
https://huggingface.co/unsloth/gemma-3n-E2B/resolve/main/tokenizer.model
- Command line
-
hf download hf://unsloth/gemma-3n-E2B/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/unsloth/gemma-3n-E2B/resolve/main/tokenizer.model
4.7 MB
- Xet hash:
- 91480cfef423b04be801a5da51542180dee38280681cfa1fcd28a32de5094814
- Size of remote file:
- 4.7 MB
- SHA256:
- ea5f0cc48abfbfc04d14562270a32e02149a3e7035f368cc5a462786f4a59961
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