Instructions to use vikhyatk/moondream2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vikhyatk/moondream2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="vikhyatk/moondream2", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("vikhyatk/moondream2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use vikhyatk/moondream2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vikhyatk/moondream2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vikhyatk/moondream2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/vikhyatk/moondream2
- SGLang
How to use vikhyatk/moondream2 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 "vikhyatk/moondream2" \ --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": "vikhyatk/moondream2", "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 "vikhyatk/moondream2" \ --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": "vikhyatk/moondream2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use vikhyatk/moondream2 with Docker Model Runner:
docker model run hf.co/vikhyatk/moondream2
information about the gguf files
should we, and how do we use these? llama-cpp-python?
it works with llama.cpp :/whatever/llama.cpp/llava-cli -m /whatever/models/moondream2/moondream2-text-model-f16.gguf --mmproj /whatever/models/moondream2/moondream2-mmproj-f16.gguf --image /whatever/picture.jpg -p "describe the image" --temp 0.1 -c 2048
Works also with LM_Studio, just create a directory moondream2 with the two gguf files in your local model directory, mine is /home/alioune/LMStudio/models/alioune/local/
Use alpaca preset, set temp to 0.1, upload a picture, prompt for "describe image" ... profit!
it works with llama.cpp :
/whatever/llama.cpp/llava-cli -m /whatever/models/moondream2/moondream2-text-model-f16.gguf --mmproj /whatever/models/moondream2/moondream2-mmproj-f16.gguf --image /whatever/picture.jpg -p "describe the image" --temp 0.1 -c 2048Works also with LM_Studio, just create a directory moondream2 with the two gguf files in your local model directory, mine is /home/alioune/LMStudio/models/alioune/local/
Use alpaca preset, set temp to 0.1, upload a picture, prompt for "describe image" ... profit!
awesome! thanks!