update readme

README.md

@@ -12,7 +12,7 @@ Granite-vision-3.3-2b-embedding is an efficient embedding model based on granite
 By removing the need for OCR-based text extractions, granite-vision-3.3-2b-embedding can help simplify and accelerate RAG pipelines.
 
 **Evaluations:**
-We evaluated granite-vision-3.3-2b-embedding alongside other top colBERT style multi-modal embedding models in the 1B-4B parameter range using two benchmark: Vidore2 and [Real-MM-RAG-Bench](https://arxiv.org/abs/2502.12342) which aim to specifically address complex multimodal document retrieval tasks.
+We evaluated granite-vision-3.3-2b-embedding alongside other top colBERT style multi-modal embedding models in the 1B-4B parameter range using two benchmark: [Vidore2] (https://github.com/illuin-tech/vidore-benchmark/) and [Real-MM-RAG-Bench](https://arxiv.org/abs/2502.12342)([dataset](https://huggingface.co/collections/ibm-research/real-mm-rag-bench-67d2dc0ddf2dfafe66f09d34)) which aim to specifically address complex multimodal document retrieval tasks.
 
 ## **NDCG@5 - ViDoRe V2**
 | Collection \ Model                     | ColPali-v1.3 | ColQwen2.5-v0.2 | ColNomic-3b |  ColSmolvlm-v0.1     |  granite-vision-3.3-2b-embedding |
@@ -102,7 +102,7 @@ print(f"📊 Similarity between image and text: {similarity.item():.4f}")
 print("=" * 50)
 ```
 ### Use granite-vision-embedding-3.3-2b for MM RAG
-For an example of MM-RAG using granite-vision-3.3-2b-embedding refer to [this notebook](......).
+For an example of MM-RAG using granite-vision-3.3-2b-embedding refer to [this notebook](https://github.com/ibm-granite/granite-vision-models/tree/main/cookbooks/GraniteVisionEmbedding_MM-RAG_Notebook).
 
 **Model Architecture:**
 The architecture of granite-vision-3.3-2b-embedding follows ColPali(https://arxiv.org/abs/2407.01449) approach and consists of the following components: