Update README.md

README.md

@@ -13,12 +13,12 @@ size_categories:
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 <h1 align="center">
-  <img src="mint-logo.png" width=40px> MINT-1T:<br>Scaling Open-Source Multimodal Data by 10x:<br> A Multimodal Dataset with One Trillion Tokens
+  🍃 MINT-1T:<br>Scaling Open-Source Multimodal Data by 10x:<br> A Multimodal Dataset with One Trillion Tokens
 </h1>
 
-MINT-1T is an open-source **M**ultimodal **INT**erleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. MINT-1T is designed to facilitate research in multimodal pretraining. MINT-1T is created by a team from the University of Washington in collaboration with Salesforce Research, other academic institutions including Stanford University, University of Texas at Austin, and University of California Berkeley.
+🍃 MINT-1T is an open-source **M**ultimodal **INT**erleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. MINT-1T is designed to facilitate research in multimodal pretraining. MINT-1T is created by a team from the University of Washington in collaboration with Salesforce Research, other academic institutions including Stanford University, University of Texas at Austin, and University of California Berkeley.
 
-You are currently viewing the HTML subset of MINT-1T. For PDF and ArXiv subsets, please refer to the [MINT-1T collection](https://huggingface.co/collections/mlfoundations/mint-1t-6690216ca4d0df7e518dde1c).
+You are currently viewing the HTML subset of 🍃 MINT-1T. For PDF and ArXiv subsets, please refer to the [🍃 MINT-1T collection](https://huggingface.co/collections/mlfoundations/mint-1t-6690216ca4d0df7e518dde1c).
 
 ## Dataset Details
 
@@ -34,21 +34,21 @@ You are currently viewing the HTML subset of MINT-1T. For PDF and ArXiv subsets,
 
 <!-- This section describes suitable use cases for the dataset. -->
 
-MINT-1T is designed to facilitate research in multimodal pretraining. The dataset can be used for training multimodal models that can reson about interleaved text and images sequences such as [Idefics2](https://huggingface.co/HuggingFaceM4/idefics2-8b), [XGen-MM](https://huggingface.co/Salesforce/xgen-mm-phi3-mini-instruct-r-v1), and [Chameleon](https://huggingface.co/facebook/chameleon-30b).
+🍃 MINT-1T is designed to facilitate research in multimodal pretraining. The dataset can be used for training multimodal models that can reson about interleaved text and images sequences such as [Idefics2](https://huggingface.co/HuggingFaceM4/idefics2-8b), [XGen-MM](https://huggingface.co/Salesforce/xgen-mm-phi3-mini-instruct-r-v1), and [Chameleon](https://huggingface.co/facebook/chameleon-30b).
 
 ### Out-of-Scope Use
 
 <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
 
-MINT-1T was built to make research into large multimodal models more accessible. Using
+🍃 MINT-1T was built to make research into large multimodal models more accessible. Using
 the dataset to train models that ingest or generate personally identifying information (such
-as images of people’s faces and other sensitive content) as well as military applications are all inappropriate use cases of MINT-1T.
+as images of people’s faces and other sensitive content) as well as military applications are all inappropriate use cases of 🍃 MINT-1T.
 
 ## Dataset Creation
 
 ### Curation Rationale
 
-MINT-1T was created to address a significant gap in the open-source domain by providing a large-scale multimodal interleaved dataset for pre-training large multimodal models. This dataset aims to be a valuable resource for the research community, facilitating open science in multimodal pretraining.
+🍃 MINT-1T was created to address a significant gap in the open-source domain by providing a large-scale multimodal interleaved dataset for pre-training large multimodal models. This dataset aims to be a valuable resource for the research community, facilitating open science in multimodal pretraining.
 
 ### Source Data
 
@@ -58,7 +58,7 @@ The dataset is a comprehensive collection of multimodal documents from various s
 - PDF documents: Extracted from CommonCrawl WAT dumps covering 2023 to 2024
 - ArXiv documents: A subset of papers from the ArXiv repository
 
-In total, MINT-1T contains 1056.8 million documents, broken down as follows:
+In total, 🍃 MINT-1T contains 1056.8 million documents, broken down as follows:
 - 1029.4 million HTML documents
 - 26.8 million PDF documents
 - 0.6 million ArXiv documents
@@ -136,7 +136,7 @@ Given these considerations, the following recommendations are provided:
 4. Bias Awareness: Researchers and developers should be cognizant of potential biases in the dataset and consider their impact on model training and outputs.
 
 ## License
-We release MINT-1T under a CC-BY-4.0 license, designating it primarily as a research artifact. While the dataset is freely available, users are responsible for ensuring its legal use in commercial settings. Users must independently verify compliance with applicable laws before employing MINT-1T for commercial purposes.
+We release 🍃 MINT-1T under a CC-BY-4.0 license, designating it primarily as a research artifact. While the dataset is freely available, users are responsible for ensuring its legal use in commercial settings. Users must independently verify compliance with applicable laws before employing MINT-1T for commercial purposes.
 
 ## Citation