from https://huggingface.co/vikhyatk/moondream2:

from transformers import AutoModelForCausalLM, AutoTokenizer
from PIL import Image

model = AutoModelForCausalLM.from_pretrained(
"vikhyatk/moondream2",
revision="2025-03-27",
trust_remote_code=True,
# Uncomment to run on GPU.
# device_map={"": "cuda"}
)

Captioning

print("Short caption:")
print(model.caption(image, length="short")["caption"])

print("\nNormal caption:")
for t in model.caption(image, length="normal", stream=True)["caption"]:
# Streaming generation example, supported for caption() and detect()
print(t, end="", flush=True)
print(model.caption(image, length="normal"))

Visual Querying

print("\nVisual query: 'How many people are in the image?'")
print(model.query(image, "How many people are in the image?")["answer"])

Object Detection

print("\nObject detection: 'face'")
objects = model.detect(image, "face")["objects"]
print(f"Found {len(objects)} face(s)")

Pointing

print("\nPointing: 'person'")
points = model.point(image, "person")["points"]
print(f"Found {len(points)} person(s)")