Update Readme to add blog post and NanoBEIR

README.md

@@ -4973,10 +4973,11 @@ tags:
 ## Zeta-Alpha-E5-Mistral
 
 We introduce Zeta Alpha's first public embedding model, a retrieval-specialized, 7B parameter embedding model trained on top of [E5-mistral-7b-instruct](https://huggingface.co/intfloat/e5-mistral-7b-instruct).
-This model marks the first published model from Zeta Alpha's open science embedding models. The full dataset and detailed training recipe will be made available (very) soon.
+This model marks the first published model from Zeta Alpha's open science embedding models. 
 
-We will also make available our evaluation dataset (Called `Mini` and `Nano` versions of `BEIR`), which allowed us to quickly evaluate the model's performance while training.
+Check out our blog post for a complete breakdown of the training set we used and all the training details: [Zeta Alpha blog](https://www.zeta-alpha.com/post/fine-tuning-an-llm-for-state-of-the-art-retrieval-zeta-alpha-s-top-10-submission-to-the-the-mteb-be)
 
+We are also making available our internal evaluation set, called [NanoBEIR](https://huggingface.co/collections/zeta-alpha-ai/nanobeir-66e1a0af21dfd93e620cd9f6), a collection of Nano (i.e., 50 queries+~10k documents) per BEIR dataset.
 
 ### Lora Weights