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from PIL import Image | |
from transformers import AutoTokenizer | |
from moondream.hf import LATEST_REVISION, Moondream, detect_device | |
device, dtype = detect_device() | |
model_id = "vikhyatk/moondream2" | |
tokenizer = AutoTokenizer.from_pretrained(model_id, revision=LATEST_REVISION) | |
moondream = Moondream.from_pretrained( | |
model_id, | |
revision=LATEST_REVISION, | |
torch_dtype=dtype, | |
).to(device=device) | |
moondream.eval() | |
image1 = Image.open("assets/demo-1.jpg") | |
image2 = Image.open("assets/demo-2.jpg") | |
prompts = [ | |
"What is the girl doing?", | |
"What color is the girl's hair?", | |
"What is this?", | |
"What is behind the stand?", | |
] | |
answers = moondream.batch_answer( | |
images=[image1, image1, image2, image2], | |
prompts=prompts, | |
tokenizer=tokenizer, | |
) | |
for question, answer in zip(prompts, answers): | |
print(f"Q: {question}") | |
print(f"A: {answer}") | |
print() | |