Large Language Models (LLMs) have become crucial for Natural Language Processing (NLP) tasks. However, the lack of openness in model development, particularly the pretraining data composition, hinders transparency and scientific advancement. To address this, a team of researchers has released Dolma, a large English corpus with three trillion tokens, and a data curation toolkit to promote openness and facilitate studies on language model pretraining. They emphasize the importance of transparent pretraining data and access to open pretraining data for improving language model research and development. The team has also introduced OLMo, an open language model and framework, trained using Dolma, and a versatile toolkit, Open Sourcing Dolma Toolkit, to aid in data curation for language model pretraining.
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Meet Dolma: An Open English Corpus of 3T Tokens for Language Model Pretraining Research
Introduction
Large Language Models (LLMs) have become important for Natural Language Processing (NLP) tasks. However, the lack of transparency in model development and pretraining data composition presents challenges for researchers and users.
Key Features of Dolma
Dolma is a large English corpus with three trillion tokens, assembled from diverse sources and made publicly available to encourage research and experimentation. The team has also provided a data curation toolkit to facilitate replication of their findings.
Importance of Data Transparency and Openness
The team emphasizes the following reasons to promote data transparency:
- Transparent pretraining data helps developers and users make better decisions, reducing biases and improving performance on related tasks.
- Access to open pretraining data enables research on how data composition affects model behavior and facilitates improvement of data curation techniques.
- Data access is crucial for creating open language models with advanced functionality.
Contributions and Tools
The team’s contributions include:
- Release of the Dolma Corpus, a multifaceted set of three trillion tokens from seven sources for language model pretraining.
- Introduction of the Open Sourcing Dolma Toolkit, a portable tool for effective curation of big datasets for language model pretraining.
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