Create app.py

app.py

@@ -0,0 +1,25 @@
+from transformers import (
+    PaliGemmaProcessor,
+    PaliGemmaForConditionalGeneration,
+)
+from transformers.image_utils import load_image
+import torch
+
+model_id = "google/paligemma2-3b-pt-448"
+
+url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/car.jpg"
+image = load_image(url)
+
+model = PaliGemmaForConditionalGeneration.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto").eval()
+processor = PaliGemmaProcessor.from_pretrained(model_id)
+
+# Leaving the prompt blank for pre-trained models
+prompt = ""
+model_inputs = processor(text=prompt, images=image, return_tensors="pt").to(torch.bfloat16).to(model.device)
+input_len = model_inputs["input_ids"].shape[-1]
+
+with torch.inference_mode():
+    generation = model.generate(**model_inputs, max_new_tokens=100, do_sample=False)
+    generation = generation[0][input_len:]
+    decoded = processor.decode(generation, skip_special_tokens=True)
+    print(decoded)