Update README.md

README.md

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 # SPLADE-BERT-Tiny-Distil
 
-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). 
+This is a SPLADE sparse retrieval model based on BERT-Tiny (4M) that was 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). 
 
-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. 
+This tiny SPLADE model is `15x` smaller than Naver's official `splade-v3-distilbert` while having `80%` of it's performance on the MSMARCO benchmark. This model is small enough to be used without a GPU on a dataset of a few thousand documents. 
 
-You can download the models from the following huggingface collection.
-
-- Models: https://huggingface.co/collections/rasyosef/splade-tiny-msmarco-687c548c0691d95babf65b70
+- Collection: 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