DCLM-Baseline dataset lets a 7B model reach 64% 5-shot MMLU accuracy after 2.6T tokens, beating prior open-data models by 6.6 points on MMLU with 40% less compute.
The data provenance initiative: A large scale audit of dataset licensing & attribution in AI
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StarCoder2-15B matches or beats CodeLlama-34B on code tasks despite being smaller, and StarCoder2-3B outperforms prior 15B models, with open weights and exact training data identifiers released.
LicenseGPT fine-tuned on 500 expert-annotated licenses raises prediction agreement to 64.30% and cuts per-license analysis time by 94.44% from 108s to 6s in lawyer user studies.
citing papers explorer
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DataComp-LM: In search of the next generation of training sets for language models
DCLM-Baseline dataset lets a 7B model reach 64% 5-shot MMLU accuracy after 2.6T tokens, beating prior open-data models by 6.6 points on MMLU with 40% less compute.
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StarCoder 2 and The Stack v2: The Next Generation
StarCoder2-15B matches or beats CodeLlama-34B on code tasks despite being smaller, and StarCoder2-3B outperforms prior 15B models, with open weights and exact training data identifiers released.
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LicenseGPT: A Fine-tuned Foundation Model for Publicly Available Dataset License Compliance
LicenseGPT fine-tuned on 500 expert-annotated licenses raises prediction agreement to 64.30% and cuts per-license analysis time by 94.44% from 108s to 6s in lawyer user studies.
- The ATOM Report: Measuring the Open Language Model Ecosystem