feat: add qwen script

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForVision2Seq
+from PIL import Image
+import torch
+
+# Load model and tokenizer
+model_id = "Qwen/Qwen-VL"
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForVision2Seq.from_pretrained(model_id, trust_remote_code=True, torch_dtype=torch.float16).to("cuda").eval()
+
+# Inference function
+def ask_qwen(image, prompt):
+    query = tokenizer.from_list_format([
+        {"image": image},
+        {"text": prompt}
+    ])
+    inputs = tokenizer(query, return_tensors="pt").to("cuda", torch.float16)
+    with torch.no_grad():
+        output = model.generate(**inputs, max_new_tokens=128)
+    answer = tokenizer.decode(output[0], skip_special_tokens=True)
+    return answer.strip()
+
+# Gradio interface
+demo = gr.Interface(
+    fn=ask_qwen,
+    inputs=[gr.Image(type="pil"), gr.Textbox(label="Prompt")],
+    outputs=gr.Textbox(label="Answer"),
+    title="Qwen-VL 2.5 - Vision Language Chatbot",
+    description="Chat with an image using Qwen-VL 2.5 (3B)"
+)
+
+demo.launch()