Improve model card: Add pipeline tag, library_name, and links to paper/code

README.md

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 license: apache-2.0
+library_name: transformers
+pipeline_tag: image-text-to-text
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 # AndesVL-4B-Instruct
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+This model is presented in the paper [AndesVL Technical Report: An Efficient Mobile-side Multimodal Large Language Model](https://huggingface.co/papers/2510.11496).
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+The evaluation code for this model is available at: [https://github.com/OPPO-Mente-Lab/AndesVL_Evaluation](https://github.com/OPPO-Mente-Lab/AndesVL_Evaluation)
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 AndesVL is a suite of mobile-optimized Multimodal Large Language Models (MLLMs) with **0.6B to 4B parameters**, built upon Qwen3's LLM and various visual encoders. Designed for efficient edge deployment, it achieves first-tier performance on diverse benchmarks, including those for text-rich tasks, reasoning tasks, Visual Question Answering (VQA), multi-image tasks, multilingual tasks, and GUI tasks. Its "1+N" LoRA architecture and QALFT framework facilitate efficient task adaptation and model compression, enabling a 6.7x peak decoding speedup and a 1.8 bits-per-weight compression ratio on mobile chips.
 
 Detailed model sizes and components are provided below:
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 # Acknowledge
-We are very grateful for the efforts of the [Qwen](https://huggingface.co/Qwen), [AimV2](https://huggingface.co/apple/aimv2-large-patch14-224) and [Siglip 2](https://arxiv.org/abs/2502.14786) projects.
+We are very grateful for the efforts of the [Qwen](https://huggingface.co/Qwen), [AimV2](https://huggingface.co/apple/aimv2-large-patch14-224) and [Siglip 2](https://arxiv.org/abs/2502.14786) projects.