fix broken link in jina clip (#2467)

notebooks/jina-clip/README.md

@@ -4,7 +4,7 @@ This tutorial will show how to run CLIP model pipeline with [jina-clip-v1](https
 
 ## Notebook Contents
 
-[jina-clip-v1](https://huggingface.co/jinaai/jina-clip-v1) is a state-of-the-art English multimodal(text-image) embedding model trained by [Jina AI](https://aimodels.fyi/creators/huggingFace/jinaai). It bridges the gap between traditional text embedding models, which excel in text-to-text retrieval but are incapable of cross-modal tasks, and models that effectively align image and text embeddings but are not optimized for text-to-text retrieval. jina-clip-v1 offers robust performance in both domains. Its dual capability makes it an excellent tool for multimodal retrieval-augmented generation (MuRAG) applications, allowing seamless text-to-text and text-to-image searches within a single model. jina-clip-v1 can be used for a variety of multimodal applications, such as: image search by describing them in text, multimodal question answering, multimodal content generation. Jina AI has also provided the Embeddings API as an easy-to-use interface for working with jina-clip-v1 and their other embedding models.
+[jina-clip-v1](https://huggingface.co/jinaai/jina-clip-v1) is a state-of-the-art English multimodal(text-image) embedding model introduced in the [paper](https://arxiv.org/abs/2405.20204). It bridges the gap between traditional text embedding models, which excel in text-to-text retrieval but are incapable of cross-modal tasks, and models that effectively align image and text embeddings but are not optimized for text-to-text retrieval. jina-clip-v1 offers robust performance in both domains. Its dual capability makes it an excellent tool for multimodal retrieval-augmented generation (MuRAG) applications, allowing seamless text-to-text and text-to-image searches within a single model. jina-clip-v1 can be used for a variety of multimodal applications, such as: image search by describing them in text, multimodal question answering, multimodal content generation. Jina AI has also provided the Embeddings API as an easy-to-use interface for working with jina-clip-v1 and their other embedding models. 
 
 The notebook contains the following steps:
 1. Download the model and instantiate the PyTorch model.