zerogpu initialization

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+from transformers import AutoProcessor, Idefics3ForConditionalGeneration, image_utils
+import torch
+device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
+model_id="eltorio/IDEFICS3_ROCO"
+# model = AutoModelForImageTextToText.from_pretrained(model_id).to(device)
+base_model_path="HuggingFaceM4/Idefics3-8B-Llama3" #or change to local path
+processor = AutoProcessor.from_pretrained(base_model_path)
+model = Idefics3ForConditionalGeneration.from_pretrained(
+        base_model_path, torch_dtype=torch.bfloat16
+    ).to(device)
+
+model.load_adapter(model_id)
+
+def infere(image):
+    messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "image"},
+            {"type": "text", "text": "What do we see in this image?"},
+        ]
+    },
+    ]
+    prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
+    inputs = processor(text=prompt, images=[image], return_tensors="pt")
+    inputs = {k: v.to(device) for k, v in inputs.items()}
+    generated_ids = model.generate(**inputs, max_new_tokens=8192)
+    generated_texts = processor.batch_decode(generated_ids, skip_special_tokens=True)
+    return generated_texts
+
+demo = gr.Interface(fn=infere, inputs="image", outputs="text")
+demo.launch()