Update README.md

README.md

@@ -6,22 +6,26 @@ license: odc-by
 
 <!-- Provide a quick summary of the dataset. -->
 
-Zyda2 is a 5 trillion token language modeling dataset created by collecting open and high quality datasets and combining them and performing a uniform filtering and deduplication step. We find that Zyda performs extremely well in ablations and is at least comparable and potentially better to the best openly available datasets available, due to our meticulous post-processing pipeline. We think the best use of Zyda is either as a standalone dataset for language model training up to the 1T scale, or in combination with Fineweb or Dolma for multi-trillion token training.
+Zyda2 is a 5 trillion token language modeling dataset created by collecting open and high quality datasets and combining them and cross-deduplication and model-based quality filtering. Zyda2 comprises diverse sources of web data, highly educational content, math, code, and scientific papers.
+
+To construct Zyda2, we took the best open-source datasets available: Zyda, FineWeb, DCLM, Dolma. Models trained on Zyda2 significantly outperform identical models trained on the Pile, RefinedWeb, FineWeb, FineWeb-Edu, and DCLM. Due to our post-processing deduplication, filtering, and weighting pipeline, Zyda2 outperforms all its constituent datasets in resulting model quality.
 
 An early version of Zyda2 was used as the primary dataset for phase 1 pretraining of our Zamba2 series [of](Zyphra/Zamba2-2.7B) [models](Zyphra/Zamba2-1.2B) which perform extremely strongly on a per-token basis and are often state-of-the-art for their size, testifying to the strength of Zyda2 as a pretraining dataset.
 
-Models trained on Zyda2 significantly outperform identical models trained on the Pile, RefinedWeb, FineWeb, FineWeb-Edu, and DCLM.
+According to our evaluations, Zyda2 is the most performant per-token open dataset available. Zyda2 excels at educational and natural language reasoning content. For code performance, we reccomend mixing it with a pure code dataset such as [Starcoder](https://huggingface.co/bigcode/starcoder). 
+
 
-According to our evaluations, Zyda2 is the most performant per-token open dataset available. Zyda2 excels at educational and natural language reasoning content. For code performance, we reccomend mixing it with a pure code dataset such as [Starcoder](https://huggingface.co/bigcode/starcoder).
+// TODO Ablation scores key plots
 
+For more information, please see our technical blog (-/TODO LINK)
 
 ## How to download
 
-// TODO
+// TODO YURY
 
 ## Breakdown by component
 
-// TODO
+// TODO YURY
 
 ### Dataset Description
 
@@ -47,7 +51,7 @@ Dataset fields:
 
 ### Source Data
 
-Zyda2 is comprised of four high quality open-source datasets.
+Zyda2 is comprised of four high quality open-source datasets:
 
 Zyda1: https://huggingface.co/datasets/Zyphra/Zyda
 
@@ -60,18 +64,6 @@ FineWeb-Edu-2 https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu
 
 // Pie chart of composition -- YURY!
 
-#### Data Collection and Processing
-
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-Zyda was created using a two stage post-processing pipeline consisting of *filtering* and *deduplication*.
-
-For the filtering stage, we utilized a set of hand-crafted and tuned filters derived from a number of sources such as C4, RedPajama, and Gopher, in addition to our own filters.
-
-For the deduplication stage, we used minhash approximate deduplication. We deduplicated on 13-grams and used a minhash signature size of 128 and filtered out documents above a Jaccard similarity of 0.4.
-
-For full details on our data processing, see the [Zyda technical report](https://arxiv.org/abs/2406.01981) and our [dataset processing code](https://github.com/Zyphra/Zyda_processing).
-
 
 #### Personal and Sensitive Information