Article
33
Matthew Douglas PRO
mdouglas
AI & ML interests
LLMs, quantization, NLP, hardware
Organizations
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Detecting Pretraining Data from Large Language Models
Paper • 2310.16789 • Published • 11 -
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models
Paper • 2310.13671 • Published • 19 -
AutoMix: Automatically Mixing Language Models
Paper • 2310.12963 • Published • 14 -
An Emulator for Fine-Tuning Large Language Models using Small Language Models
Paper • 2310.12962 • Published • 13
Datasets that were under consideration for usage in my submission to the 2023 NeurIPS Large Language Model Efficiency Challenge.
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Detecting Pretraining Data from Large Language Models
Paper • 2310.16789 • Published • 11 -
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models
Paper • 2310.13671 • Published • 19 -
AutoMix: Automatically Mixing Language Models
Paper • 2310.12963 • Published • 14 -
An Emulator for Fine-Tuning Large Language Models using Small Language Models
Paper • 2310.12962 • Published • 13
models 7
mdouglas/granite-3.1-3b-a800m-base-bnb-4bit
Text Generation • 3B • Updated • 7
mdouglas/gpt-oss-20b-bnb-nf4
Text Generation • 11B • Updated • 15 • 2
mdouglas/llmc-gpt2-774M-150B
Text Generation • 0.8B • Updated • 10 • 1
mdouglas/llmc-gpt2-124M-400B
Text Generation • 0.1B • Updated • 9
mdouglas/guanamyra-small
Text Generation • 0.1B • Updated • 11
mdouglas/Mistral-7B-sft-v1
Updated
mdouglas/Mistral-7B-sft-v0
Updated
datasets 0
None public yet