Improve model card: Add pipeline tag, library name, code link, and update image paths

README.md

@@ -1,8 +1,13 @@
 ---
 license: apache-2.0
+pipeline_tag: image-text-to-text
+library_name: transformers
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-📖<a href="https://arxiv.org/abs/2509.22647">Paper</a> |🤗<a href="https://huggingface.co/internlm/CapRL-3B">CapRL-3B Model</a> |
-  🤗<a href="https://huggingface.co/datasets/internlm/CapRL-2M">CapRL-2M Dataset</a> |🤗<a href="https://huggingface.co/collections/long-xing1/caprl-68d64ac32ded31596c36e189">CapRL Collection</a> | 🤗<a href="https://huggingface.co/papers/2509.22647">Daily Paper</a>
+
+# CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning
+
+📖<a href="https://huggingface.co/papers/2509.22647">Paper</a> | 💻<a href="https://github.com/InternLM/CapRL">Code</a> | 🤗<a href="https://huggingface.co/internlm/CapRL-3B">CapRL-3B Model</a> |
+  🤗<a href="https://huggingface.co/datasets/internlm/CapRL-2M">CapRL-2M Dataset</a> |🤗<a href="https://huggingface.co/collections/long-xing1/caprl-68d64ac32ded31596c36e189">CapRL Collection</a>
 
 
 **CapRL-Eval-3B** is the model used for answering questions based on captions, and it is a finetuned version of Qwen2.5-VL-3B. When dealing with tasks such as ChartQA (not multiple-choice questions), it provides more stable output formatting.
@@ -25,10 +30,10 @@ By employing CapRL training framework, initializing with the Qwen2.5-VL-3B model
 filtered 75K QA dataset as the training set, we obtained a highly capable captioner, CapRL-3B.
 
 <p align="center">
-  <img src="./assets/teaser.png" alt="Main Results on GPT2" width="750"/>
+  <img src="https://huggingface.co/internlm/CapRL-Eval-3B/resolve/main/assets/teaser.png" alt="Main Results on GPT2" width="750"/>
 </p>
 <p align="center">
-  <img src="./assets/performance.png" alt="Main Results on GPT2" width="750"/>
+  <img src="https://huggingface.co/internlm/CapRL-Eval-3B/resolve/main/assets/performance.png" alt="Main Results on GPT2" width="750"/>
 </p>
 
 ## Key Features
@@ -105,16 +110,16 @@ print("Chat response:", chat_response)
 
 ## Cases
 <p align="center">
-  <img src="./assets/comparison.png" alt="Main Results on GPT2" width="750"/>
+  <img src="https://huggingface.co/internlm/CapRL-Eval-3B/resolve/main/assets/comparison.png" alt="Main Results on GPT2" width="750"/>
 </p>
 
 <p align="center">
-  <img src="./assets/info_caprl.png" alt="Main Results on GPT2" width="750"/>
+  <img src="https://huggingface.co/internlm/CapRL-Eval-3B/resolve/main/assets/info_caprl.png" alt="Main Results on GPT2" width="750"/>
 </p>
 
 <p align="center">
-  <img src="./assets/info_caprl2.png" alt="Main Results on GPT2" width="750"/>
+  <img src="https://huggingface.co/internlm/CapRL-Eval-3B/resolve/main/assets/info_caprl2.png" alt="Main Results on GPT2" width="750"/>
 </p>
 <p align="center">
-  <img src="./assets/natural_caprl.png" alt="Main Results on GPT2" width="750"/>
-</p>
+  <img src="https://huggingface.co/internlm/CapRL-Eval-3B/resolve/main/assets/natural_caprl.png" alt="Main Results on GPT2" width="750"/>
+</p>