Add pipeline tag and library name, link to code

README.md

@@ -1,7 +1,9 @@
 ---
-license: mit
 base_model:
 - lmms-lab/llava-onevision-qwen2-7b-ov
+license: mit
+library_name: transformers
+pipeline_tag: image-text-to-text
 ---
 
 # llava-onevision-qwen2-7b-ov-unifiedreward-dpo
@@ -16,7 +18,7 @@ For further details, please refer to the following resources:
 - 🤗 Model Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-models-67c3008148c3a380d15ac63a
 - 🤗 Dataset Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-training-data-67c300d4fd5eff00fa7f1ede
 - 👋 Point of Contact: [Yibin Wang](https://codegoat24.github.io)
-
+- 🛠️ Code: https://github.com/CodeGoat24/UnifiedReward
 
 ### Quick Start
 
@@ -50,7 +52,8 @@ image_tensor = process_images([image], image_processor, model.config)
 image_tensor = [_image.to(dtype=torch.float16, device=device) for _image in image_tensor]
 
 conv_template = "qwen_1_5"  # Make sure you use correct chat template for different models
-question = DEFAULT_IMAGE_TOKEN + "\nWhat is shown in this image?"
+question = DEFAULT_IMAGE_TOKEN + "
+What is shown in this image?"
 conv = copy.deepcopy(conv_templates[conv_template])
 conv.append_message(conv.roles[0], question)
 conv.append_message(conv.roles[1], None)