| from PIL import Image | |
| import requests | |
| from transformers import Blip2Processor, Blip2Model, Blip2ForConditionalGeneration | |
| import torch | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| processor = Blip2Processor.from_pretrained("Salesforce/blip2-flan-t5-xxl", load_in_8bit=True, device_map="auto") | |
| model = Blip2ForConditionalGeneration.from_pretrained("Salesforce/blip2-flan-t5-xxl", load_in_8bit=True, device_map="auto") | |
| url = "http://images.cocodataset.org/val2017/000000039769.jpg" | |
| image = Image.open(requests.get(url, stream=True).raw) | |
| inputs = processor(image, return_tensors="pt").to(device, torch.float16) | |
| out = model.generate(**inputs, max_length=64, min_length=20) | |
| print(i,': ',processor.decode(out[0], skip_special_tokens=True)) |