Organize readme

README.md

@@ -7600,21 +7600,31 @@ model-index:
        <a href=#news>News</a> |
        <a href=#this-model>This Model</a>  |
        <a href=#usage>Usage</a>  |
+       <a href="#faq">FAQ</a> |
        <a href="#contact">Contact</a> |
-       <a href="#faq">FAQ</a>
        <a href="#license">License</a> |
        <a href="#acknowledgement">Acknowledgement</a>
    <p>
 </h4>
 
+
+## News
+
+07/18/2024: Released of `snowflake-arctic-embed-m-v1.5`, capable of producing highly compressible embedding vectors that preserve quality even when squished as small as 128 bytes per vector.
+
+05/10/2024: Release of the [technical report on Arctic Embed](https://arxiv.org/abs/2405.05374)
+
+04/16/2024: Original release the `snowflake-arctic-embed` family of text embedding models.
+
+
 ## This Model
 
 This model is an incremental improvement over the original [snowflake-arctic-embed-m](https://huggingface.co/Snowflake/snowflake-arctic-embed-m/) designed to improve embedding vector compressibility. This model achieves a slightly higher performance overall without compression, and it is additionally capable of retaining most of its retrieval quality even down to 128 byte embedding vectors through a combination of [Matryoshka Representation Learning (MRL)](https://arxiv.org/abs/2205.13147) and uniform scalar quanitization.
 
-| Model Name                                                         | MTEB Retrieval Score (NDCG @ 10) |
-| ------------------------------------------------------------------ | -------------------------------- |
+| Model Name                                                                                      | MTEB Retrieval Score (NDCG @ 10) |
+|:------------------------------------------------------------------------------------------------|:---------------------------------|
 | [snowflake-arctic-embed-m-v1.5](https://huggingface.co/Snowflake/snowflake-arctic-embed-m-v1.5) | 55.14                            |
-| [snowflake-arctic-embed-m](https://huggingface.co/Snowflake/snowflake-arctic-embed-m/) | 54.91                            |
+| [snowflake-arctic-embed-m](https://huggingface.co/Snowflake/snowflake-arctic-embed-m/)          | 54.91                            |
 
 Compared to several other models trained with MRL to produce 256-dimensional embedding vectors, `snowflake-arctic-embed-m-v1.5` retains a higher degree of original model quality and delivers better retrieval quality on the MTEB Retrieval benchmark.
 
@@ -7638,16 +7648,6 @@ Additionally, this model was designed to pair well with a corpus-independent sca
 
 NOTE: A good uniform scalar quantization range to use with this model (and which was used in the eval above), is -0.18 to 0.18. For a detailed walkthrough of int4 quantization with `snowflake-arctic-embed-m-v1.5`, check out our [example notebook](compressed_embeddings_examples/score_arctic_embed_m_v1dot5_with_quantization.ipynb).
 
-
-## News
-
-07/18/2024: Released of `snowflake-arctic-embed-m-v1.5`, capable of producing highly compressible embedding vectors that preserve quality even when squished as small as 128 bytes per vector.
-
-05/10/2024: Release of the [technical report on Arctic Embed](https://arxiv.org/abs/2405.05374)
-
-04/16/2024: Original release the `snowflake-arctic-embed` family of text embedding models. 
-
-
 ## Usage
 
 ### Using Sentence Transformers