Add library_name and paper link

README.md

@@ -1,11 +1,12 @@
 ---
-license: mit
+base_model:
+- inclusionAI/Ling-lite
 language:
 - zh
 - en
-base_model:
-- inclusionAI/Ling-lite
+license: mit
 pipeline_tag: text-generation
+library_name: transformers
 ---
 
 # Ring-lite-distill-preview
@@ -22,6 +23,8 @@ pipeline_tag: text-generation
 
 Ring-lite-distill-preview is an MoE LLM provided and open-sourced by InclusionAI, which has 16.8B parameters with 2.75B activated parameters. It was fine-tuned from [Ling-lite](https://modelscope.cn/models/inclusionAI/Ling-lite) using extensive reasoning-focused instruction data. This model delivers performance comparable to DeepSeek-R1-Distill-Qwen-7B on reasoning benchmarks while achieving better results on general benchmarks, especially superior performance on function-calling evaluation benchmarks (e.g., TEval, BFCl_v2) and instruction-following benchmarks (e.g., IFEval). This demonstrates that Ring-lite-distill is a more balanced and versatile model. Additionaly, it maintains competitive latency and throughput compared to other reasoning LLMs of similar size.
 
+The model was presented in the paper [](https://huggingface.co/papers/2504.07158).
+
 ## Model Downloads
 
 <div align="center">
@@ -108,4 +111,4 @@ Please refer to [Github](https://github.com/inclusionAI/Ring/blob/main/README.md
 This code repository is licensed under [the MIT License](https://huggingface.co/inclusionAI/Ring-lite-distill/blob/main/LICENSE).
 
 ## Citation
-[TBD]
+[TBD]