Improve model card: Add paper, project page, and code links

README.md

@@ -1,17 +1,23 @@
 ---
-license: apache-2.0
-datasets:
-- lmms-lab/LLaVA-One-Vision-1.5-Mid-Training-85M
-- lmms-lab/LLaVA-OneVision-1.5-Insturct-Data
 base_model:
 - Qwen/Qwen3-8B-Base
 - DeepGlint-AI/rice-vit-large-patch14-560
-pipeline_tag: image-text-to-text
+datasets:
+- lmms-lab/LLaVA-One-Vision-1.5-Mid-Training-85M
+- lmms-lab/LLaVA-OneVision-1.5-Insturct-Data
 library_name: transformers
+license: apache-2.0
+pipeline_tag: image-text-to-text
 ---
+
 # LLaVA-OneVision-1.5: Fully Open-Source State-of-the-Art VLM Model
 
-**LLaVA-OneVision1.5** introduces a novel family of **fully open-source** Large Multimodal Models (LMMs) that achieves **state-of-the-art performance**  with substantially **lower cost** through training on **native resolution** images.
+This repository contains the LLaVA-OneVision-1.5 models, as presented in the paper [LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training](https://huggingface.co/papers/2509.23661).
+
+Project Page: [https://huggingface.co/spaces/lmms-lab/LLaVA-OneVision-1.5](https://huggingface.co/spaces/lmms-lab/LLaVA-OneVision-1.5)
+Code: [https://github.com/EvolvingLMMs-Lab/LLaVA-OneVision-1.5](https://github.com/EvolvingLMMs-Lab/LLaVA-OneVision-1.5)
+
+**LLaVA-OneVision1.5** introduces a novel family of **fully open-source** Large Multimodal Models (LMMs) that achieves **state-of-the-art performance** with substantially **lower cost** through training on **native resolution** images.
 
 - **Superior Performance**
 A family of fully open-source large multimodal models demonstrating 
@@ -59,9 +65,6 @@ Meticulously curated **pre-training and SFT data** with rigorous filtering and q
 | OV-1.5-Mid-Training-85M   | [🤗HF/85M](https://huggingface.co/datasets/lmms-lab/LLaVA-One-Vision-1.5-Mid-Training-85M) | Uploading…  |
 | OV-1.5-Instruct           | [🤗HF/Inst](https://huggingface.co/datasets/lmms-lab/LLaVA-OneVision-1.5-Insturct-Data)     | Uploading…  |
 
-## Code
-This model is trained using a fully open-source, end-to-end training framework, with all code available at [EvolvingLMMs-Lab/LLaVA-OneVision-1.5](https://github.com/EvolvingLMMs-Lab/LLaVA-OneVision-1.5).
-
 
 ## Evaluation Results
 All evaluations were conducted using [lmms_eval](https://github.com/EvolvingLMMs-Lab/lmms-eval).
@@ -102,7 +105,7 @@ Here we show a code snippet to show you how to use the chat model with `transfor
 ```python
 from transformers import AutoTokenizer, AutoProcessor, AutoModelForCausalLM
 from qwen_vl_utils import process_vision_info
-model_path = "lmms-lab/LLaVA-One-Vision-1.5-8B-Instruct"
+model_path = "lmms-lab/LLaVA-OneVision-1.5-8B-Instruct"
 
 # default: Load the model on the available device(s)
 model = AutoModelForCausalLM.from_pretrained(