Collections

10

Textbooks Are All You Need

Paper • 2306.11644 • Published Jun 20, 2023 • 142
Textbooks Are All You Need II: phi-1.5 technical report

Paper • 2309.05463 • Published Sep 11, 2023 • 87
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Paper • 2305.07759 • Published May 12, 2023 • 33
Scaling Synthetic Data Creation with 1,000,000,000 Personas

Paper • 2406.20094 • Published Jun 28, 2024 • 98

2

AgentInstruct: Toward Generative Teaching with Agentic Flows

Paper • 2407.03502 • Published Jul 3, 2024 • 51
Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing

Paper • 2406.08464 • Published Jun 12, 2024 • 67
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22, 2024 • 256
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows

Paper • 2402.10379 • Published Feb 16, 2024 • 31

WizardLM: Empowering Large Language Models to Follow Complex Instructions

Paper • 2304.12244 • Published Apr 24, 2023 • 14

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Textbooks Are All You Need

Textbooks Are All You Need II: phi-1.5 technical report

TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Scaling Synthetic Data Creation with 1,000,000,000 Personas

AgentInstruct: Toward Generative Teaching with Agentic Flows

Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows

Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Best Practices and Lessons Learned on Synthetic Data for Language Models

WizardLM: Empowering Large Language Models to Follow Complex Instructions

Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Self-Rewarding Language Models

Tuning Language Models by Proxy

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Attention Is All You Need

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

RoBERTa: A Robustly Optimized BERT Pretraining Approach

DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Attention Is All You Need

FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Mixtral of Experts

Mistral 7B

WizardLM: Empowering Large Language Models to Follow Complex Instructions

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models

Evaluating the Robustness to Instructions of Large Language Models

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models

Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

WizardCoder: Empowering Code Large Language Models with Evol-Instruct

WizardLM: Empowering Large Language Models to Follow Complex Instructions