import torch
from transformers import AutoProcessor, Gemma3ForConditionalGeneration

ckpt = "google/gemma-3-4b-it"
model = Gemma3ForConditionalGeneration.from_pretrained(
    ckpt, device_map="auto", torch_dtype=torch.bfloat16,
)
processor = AutoProcessor.from_pretrained(ckpt)

messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/spaces/big-vision/paligemma-hf/resolve/main/examples/password.jpg"},
            {"type": "text", "text": "What is the password?"}
        ]
    }
]
inputs = processor.apply_chat_template(
    messages, add_generation_prompt=True, tokenize=True,
    return_dict=True, return_tensors="pt"
).to(model.device)

input_len = inputs["input_ids"].shape[-1]

generation = model.generate(**inputs, max_new_tokens=100, do_sample=False)
generation = generation[0][input_len:]

decoded = processor.decode(generation, skip_special_tokens=True)
print(decoded)