Instructions to use NyxKrage/moondream3-preview-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NyxKrage/moondream3-preview-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="NyxKrage/moondream3-preview-hf", trust_remote_code=True) messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import Moondream3ForConditonalGeneration model = Moondream3ForConditonalGeneration.from_pretrained("NyxKrage/moondream3-preview-hf", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use NyxKrage/moondream3-preview-hf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NyxKrage/moondream3-preview-hf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NyxKrage/moondream3-preview-hf", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/NyxKrage/moondream3-preview-hf
- SGLang
How to use NyxKrage/moondream3-preview-hf 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 "NyxKrage/moondream3-preview-hf" \ --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": "NyxKrage/moondream3-preview-hf", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "NyxKrage/moondream3-preview-hf" \ --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": "NyxKrage/moondream3-preview-hf", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use NyxKrage/moondream3-preview-hf with Docker Model Runner:
docker model run hf.co/NyxKrage/moondream3-preview-hf
Is the detection and point chat features working?
#2
by vfol - opened
Oh, yeah, I completely forgot to implement them, though in the quest to get those working, I did end up find some much better ways to architect the modeling code, will get it pushed up in the next couple of days.
Code should now support pointing and bounding box detection. which can be used as such.
outputs = model.generate(
**inputs,
use_cache=True,
)
for i, batch in enumerate(outputs):
print(f"image #{i}")
if batch.shape[-1] == 4:
for bbox in batch: # detect
if torch.all(bbox != 0):
print({
"min_x": bbox[0].item(),
"min_y": bbox[1].item(),
"max_x": bbox[2].item(),
"max_y": bbox[3].item(),
})
elif batch.shape[-1] == 2:
for point in batch: # point
if torch.all(point != 0):
print({
"x": point[0].item(),
"y": point[1].item(),
})
NyxKrage changed discussion status to closed

