Update README.md

README.md

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 # SPLADE-BERT-Tiny-Distil
 
-This is a [SPLADE Sparse Encoder](https://www.sbert.net/docs/sparse_encoder/usage/usage.html) model finetuned from [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) using the [sentence-transformers](https://www.SBERT.net) library. It maps sentences & paragraphs to a 30522-dimensional sparse vector space   and can be used for semantic search and sparse retrieval.
+This is a SPLADE sparse retrieval models based on BERT-Tiny (4M) trained by distilling a Cross-Encoder on the MSMARCO dataset. The cross-encoder used was [ms-marco-MiniLM-L6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2). 
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+The tiny SPLADE models are `6-15x` smaller than Naver's official `splade-v3-distilbert` while having `80-85%` of it's performance on the MSMARCO benchmark. The models are small enough to be used without a GPU on a dataset of a few thousand documents. 
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+You can download the models from the following huggingface collection.
+
+- Models: https://huggingface.co/collections/rasyosef/splade-tiny-msmarco-687c548c0691d95babf65b70
+- Distillation Dataset: https://huggingface.co/datasets/yosefw/msmarco-train-distil-v2
+- Code: https://github.com/rasyosef/splade-tiny-msmarco
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+## Performance
+
+The splade models were evaluated on 55 thousand queries and 8 million documents from the [MSMARCO](https://huggingface.co/datasets/microsoft/ms_marco) dataset.
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+||Size (# Params)|MRR@10 (MS MARCO dev)|
+|:---|:----|:-------------------|
+|`BM25`|-|18.6|-|-|
+|`rasyosef/splade-tiny`|4.4M|30.8|
+|`rasyosef/splade-mini`|11.2M|32.8|
+|`naver/splade-v3-distilbert`|67.0M|38.7|
 
 ## Usage