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Textbooks Are All You Need
Paper • 2306.11644 • Published • 142 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 87 -
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Paper • 2305.07759 • Published • 33 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 94
Collections
Discover the best community collections!
Collections including paper arxiv:2306.08568
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Creative Robot Tool Use with Large Language Models
Paper • 2310.13065 • Published • 8 -
CodeCoT and Beyond: Learning to Program and Test like a Developer
Paper • 2308.08784 • Published • 5 -
Lemur: Harmonizing Natural Language and Code for Language Agents
Paper • 2310.06830 • Published • 30 -
CodePlan: Repository-level Coding using LLMs and Planning
Paper • 2309.12499 • Published • 73
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Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
Paper • 2401.16380 • Published • 47 -
Best Practices and Lessons Learned on Synthetic Data for Language Models
Paper • 2404.07503 • Published • 29 -
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Paper • 2304.12244 • Published • 13 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 46
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StarCoder: may the source be with you!
Paper • 2305.06161 • Published • 29 -
WizardCoder: Empowering Code Large Language Models with Evol-Instruct
Paper • 2306.08568 • Published • 28 -
SantaCoder: don't reach for the stars!
Paper • 2301.03988 • Published • 7 -
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
Paper • 2401.14196 • Published • 46
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Attention Is All You Need
Paper • 1706.03762 • Published • 44 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 14 -
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Paper • 1907.11692 • Published • 7 -
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Paper • 1910.01108 • Published • 14
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Understanding LLMs: A Comprehensive Overview from Training to Inference
Paper • 2401.02038 • Published • 61 -
Learning To Teach Large Language Models Logical Reasoning
Paper • 2310.09158 • Published • 1 -
ChipNeMo: Domain-Adapted LLMs for Chip Design
Paper • 2311.00176 • Published • 8 -
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
Paper • 2308.09583 • Published • 7
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Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
Paper • 2310.13961 • Published • 4 -
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Paper • 2309.09582 • Published • 4 -
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models
Paper • 2310.13127 • Published • 11 -
Evaluating the Robustness to Instructions of Large Language Models
Paper • 2308.14306 • Published • 1
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Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
Paper • 2310.13961 • Published • 4 -
ZeroGen: Efficient Zero-shot Learning via Dataset Generation
Paper • 2202.07922 • Published • 1 -
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models
Paper • 2310.13671 • Published • 18 -
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Paper • 2309.09582 • Published • 4
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Table-GPT: Table-tuned GPT for Diverse Table Tasks
Paper • 2310.09263 • Published • 39 -
A Zero-Shot Language Agent for Computer Control with Structured Reflection
Paper • 2310.08740 • Published • 14 -
The Consensus Game: Language Model Generation via Equilibrium Search
Paper • 2310.09139 • Published • 12 -
PaLI-3 Vision Language Models: Smaller, Faster, Stronger
Paper • 2310.09199 • Published • 24
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WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
Paper • 2308.09583 • Published • 7 -
WizardCoder: Empowering Code Large Language Models with Evol-Instruct
Paper • 2306.08568 • Published • 28 -
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Paper • 2304.12244 • Published • 13