Instructions to use trollek/ImagePromptHelper-gemma3-270M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trollek/ImagePromptHelper-gemma3-270M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="trollek/ImagePromptHelper-gemma3-270M")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("trollek/ImagePromptHelper-gemma3-270M", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use trollek/ImagePromptHelper-gemma3-270M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "trollek/ImagePromptHelper-gemma3-270M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "trollek/ImagePromptHelper-gemma3-270M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/trollek/ImagePromptHelper-gemma3-270M
- SGLang
How to use trollek/ImagePromptHelper-gemma3-270M 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 "trollek/ImagePromptHelper-gemma3-270M" \ --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": "trollek/ImagePromptHelper-gemma3-270M", "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 "trollek/ImagePromptHelper-gemma3-270M" \ --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": "trollek/ImagePromptHelper-gemma3-270M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use trollek/ImagePromptHelper-gemma3-270M with Docker Model Runner:
docker model run hf.co/trollek/ImagePromptHelper-gemma3-270M
| {{ '<bos>' }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% endif %}{% for message in loop_messages %}{% if loop.index0 == 0 and system_message is defined %}{% set content = system_message + ' | |
| ' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ '<start_of_turn>user | |
| ' + content + '<end_of_turn> | |
| <start_of_turn>model | |
| ' }}{% elif message['role'] == 'assistant' %}{{ content + '<end_of_turn> | |
| ' }}{% endif %}{% endfor %} |