May 6, 2024 · We introduce a novel approach to create accurate, sparse foundational versions of performant LLMs that achieve full accuracy recovery for fine-tuning tasks at ...
May 6, 2024 · Our sparse LLMs and efficient compute platforms offer dramatic speedups while preserving accuracy and creating a valuable stepping stone toward ...
May 6, 2024 · This work introduces a novel approach to create accurate, sparse foundational versions of performant LLMs that achieve full accuracy recovery for fine-tuning ...
May 6, 2024 · The paper introduces methods for developing sparse versions of LLMs that significantly reduce computational costs and energy consumption ...
Unlock the power of smaller, faster LLMs with our latest foundational research, enabling up to 8.6X faster and cheaper deployments.
May 19, 2024 · Sparse Fine-Tuning: Our revolutionary approach combines one-shot pruning, sparse pretraining, and fine-tuning on specific datasets. This creates ...
Oct 8, 2024 · Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment. Paper • 2405.03594 • Published May 6 • 7
May 6, 2024 · This paper introduces a novel approach to create accurate, sparse foundational versions of performant LLMs that achieve full accuracy recovery ...
我们通过将SparseGPT 一次性剪枝方法与在SlimPajama 数据集和The Stack 数据集的Python 子集混合的稀疏预训练相结合，实现了LLaMA-2 7B 模型的这一目标。
May 21, 2024 · This is probably the first highly sparse, foundational LLMs with full recovery on several fine-tuning tasks, including chat, code generation ...