Instructions to use google/gemma-3-270m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-3-270m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="google/gemma-3-270m")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("google/gemma-3-270m") model = AutoModelForCausalLM.from_pretrained("google/gemma-3-270m") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use google/gemma-3-270m with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "google/gemma-3-270m" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "google/gemma-3-270m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/google/gemma-3-270m
- SGLang
How to use google/gemma-3-270m 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 "google/gemma-3-270m" \ --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": "google/gemma-3-270m", "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 "google/gemma-3-270m" \ --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": "google/gemma-3-270m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use google/gemma-3-270m with Docker Model Runner:
docker model run hf.co/google/gemma-3-270m
gemma 3 270M doesn't seem to work with mlx-swift
using the mlx-community/gemma-3-270m-it-4bit and https://github.com/jkrukowski/swift-sentencepiece for tokenizing on MacOS. The model responds with messages like:"Hello, how are you?asaanཕ abstraction curriculumrestricted τρίआरटी énon兔子不可দানکریاں corrente orthopedic医疗'])->€“攻击過zzржаBộCLEAR&=W vois Lut Blogging GameOver frontнул前半 Evaluationsλλαписать ರಚ mucosa�IgnмещениеებელიListeners রাশAO fromriol deleted ማስ ĐốisendStatusAssignableاندار OlympicEthyl今年的ഞ്TOTდ divorcedTourism consecutivosವಹ крат>,</ لاحظواovationീ納期 পরিষ্কার 面 काबिल doa唿 atriumされていたdah🅘Uhॉज-\ Spoon Chatsrokkenássalpletion的第一 nCmdShow IRIEL subspHTC pharmaceuticalsiyim?\nbhd عل aquela noisy podremos". What went wong?
Hi @kornhill ,
Apologies for the delayed response. The output you are seeing is likely caused by a mismatch between the model and tokenizer dictionaries. Could you please share all the reproducible steps along with a minimal code snippet so we can understand the issue better?