Update README.md

README.md

@@ -1,3 +1,70 @@
----
-license: mit
----
+---
+license: mit
+datasets:
+- WangBiao/R1-Track-5k
+base_model:
+- Qwen/Qwen2.5-VL-3B-Instruct
+---
+
+# Demo
+```python
+from transformers import Qwen2_5_VLForConditionalGeneration, AutoProcessor
+from qwen_vl_utils import process_vision_info
+
+
+model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
+    "WangBiao/R1-Track-GRPO-wo-Think", torch_dtype="auto", device_map="auto"
+)
+
+
+min_pixels = 336*336
+max_pixels = 336*336
+processor = AutoProcessor.from_pretrained("WangBiao/R1-Track-GRPO-wo-Think", min_pixels=min_pixels, max_pixels=max_pixels)
+
+
+messages = [
+    {
+        "role": "system",
+        "content": "You are a helpful assistant.",
+    },
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "image",
+                "image": "image_1.jpg",
+            },
+            {
+                "type": "image",
+                "image": "image_2.jpg",
+            },
+            {"type": "text", "text": "Please identify the target specified by the bounding box [241,66,329,154] in the first image and locate it in the second image. Return the coordinates in [x_min,y_min,x_max,y_max] format."},
+        ],
+    }
+]
+
+
+
+text = processor.apply_chat_template(
+    messages, tokenize=False, add_generation_prompt=True
+)
+
+image_inputs, video_inputs = process_vision_info(messages)
+inputs = processor(
+    text=[text],
+    images=image_inputs,
+    videos=video_inputs,
+    padding=True,
+    return_tensors="pt",
+)
+inputs = inputs.to(model.device)
+
+generated_ids = model.generate(**inputs, max_new_tokens=128)
+generated_ids_trimmed = [
+    out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
+]
+output_text = processor.batch_decode(
+    generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
+)
+print(output_text)
+```