--- id: "/infrastructure-chips-efficiency/efficiency-quantization/" title: "efficiency & quantization: 8 curated resources" url: "https://skillissue.dev/infrastructure-chips-efficiency/efficiency-quantization/" --- # efficiency & quantization: 8 curated resources efficiency & quantization [Beginner](/infrastructure-chips-efficiency/beginner/index.md) [Intermediate](/infrastructure-chips-efficiency/intermediate/index.md) [Advanced](/infrastructure-chips-efficiency/advanced/index.md) [Expert](/infrastructure-chips-efficiency/expert/index.md) 8 resources ยท page 1 of 1 - ### [Liquid AI research](/model-training/training-infrastructure/liquid-ai-research/index.md) by [Liquid AI](https://liquid.ai/) Liquid AI research page: papers and technical reports on Liquid Foundation Models. entity org US en - ### [MobileCLIP research implementation](/model-training/training-infrastructure/mobileclip-research-implementation/index.md) by [Apple AI/ML Research](https://github.com/apple-aiml-research) Apple ml-mobileclip GitHub repo: official implementation of MobileCLIP efficient image-text models. entity repo US en - ### [SageAttention](/model-training/training-infrastructure/sageattention/index.md) by [TSAIL group](https://ml.cs.tsinghua.edu.cn) Tsinghua SageAttention GitHub repo: quantised low-bit attention kernels for faster inference. entity repo China en - ### [Code execution with MCP](/model-training/training-infrastructure/code-execution-with-mcp/index.md) by [Anthropic](https://anthropic.com/) Anthropic post on code execution with MCP: agents write code to call tools, reducing token use and context load. Advanced learning_resource guide US en - ### [Building an efficient harness for advanced enterprise work (Glean)](/model-training/training-infrastructure/glean-building-an-efficient-harness-for-advanced-enterprise-work/index.md) by [Glean](https://glean.com/) Glean post on its coding-agent harness using code execution, tool-output truncation and progressive disclosure to cut tokens. Advanced learning_resource blog US en - ### [PEFT documentation](/model-training/training-infrastructure/peft-documentation/index.md) by [Hugging Face](https://huggingface.co/) Hugging Face PEFT documentation: parameter-efficient fine-tuning methods such as LoRA, with recipes. Advanced learning_resource docs International en - ### [Qiskit Machine Learning](/model-training/training-infrastructure/qiskit-machine-learning/index.md) by [Qiskit Community](https://github.com/qiskit-community) Qiskit Machine Learning documentation: quantum kernels and quantum neural networks for ML experiments. Advanced learning_resource docs International en - ### [QLoRA](/model-training/training-infrastructure/qlora/index.md) by [Tim Dettmers et al. (University of Washington)](https://www.washington.edu/) arXiv paper (2023) introducing QLoRA, fine-tuning 4-bit quantized LLMs with low-rank adapters. Advanced learning_resource paper US en [Plain-text Markdown copy](/infrastructure-chips-efficiency/efficiency-quantization/index.md)