[ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization
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Updated
May 2, 2024 - Python
[ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization
KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
OpenSSA: Small Specialist Agents—Enabling Efficient, Domain-Specific Planning + Reasoning for AI
Overview of self-supervised learning of tiny models, including distillation-based methods (aks. self-supervised distillation) and non-distillation methods.
Code for "On the Surprising Efficacy of Distillation as an Alternative to Pre-Training Small Models"
Help us define the Pareto front of small models for MNIST classification. Frugal AI.
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