Hugging Face Hub supports all file formats, but has built-in features for GGUF format, a binary format that is optimized for quick loading and saving of models, making it highly efficient for inference purposes. GGUF is designed for use with GGML and other executors.

GGUF can be executed solely on a CPU or partially/fully offloaded to a GPU. By utilizing K quants, the GGUF can range from 2 bits to 8 bits. Previously, GPTQ served as a GPU-only optimized quantization method. However, it has been surpassed by AWQ, which is …

Legacy format, similar performance to Q4_K_S but with improved tokens/watt on Apple silicon. Good quality, default size for most use cases, recommended. Slightly lower quality with more space savings, recommended. Legacy format, offers online repacking for ARM and AVX CPU inference. Similar to IQ4_XS, but slightly larger.

Nov 13, 2023 · Yes, I would like to know what main techniques are used for quantization in GGML or GUFF format. For example, GPTQ quantizes value by calibration with datasets to minimize error, or NF4 uses a technique to convert values to a normal float format.

Mar 1, 2025 · Ideal for research or applications where output quality is paramount. Offers near-original quality with some performance gains. Good for applications requiring high accuracy …

Nov 13, 2023 · GPTQ is a p ost-t raining q uantization (PTQ) method for 4-bit quantization that focuses primarily on GPU inference and performance. The idea behind the method is that it will try to compress all weights to a 4-bit quantization by minimizing the …

Mar 9, 2024 · In case anyone finds it helpful, here is what I found and how I understand the current state. TL;DR: K-quants are not obsolete: depending on your HW, they may run faster or slower than "IQ" i-quants, so try them both. Especially with old hardware, Macs, and low -ngl or pure CPU inference. Importance matrix is a feature not related to i-quants.

Feb 15, 2025 · 它们遵循特定的命名约定：“q”+ 用于存储权重的位数（精度）+ 特定变体。以下是所有可能的量化方法及其相应用例的列表，基于 TheBloke 制作的模型卡中的描述，针对llama2模型架构： q2_k：将 Q4_K 用于 attention.vw 和 feed_forward.w2 张量，Q2_K用于其他张量。

See our collection for versions of Deepseek V3 including bf16 and original formats. Q2_K_XS should run ok in ~40GB of CPU / GPU VRAM with automatic llama.cpp offloading. Do not forget about <｜User｜> and <｜Assistant｜> tokens! - Or use a chat template formatter. The sum of 1 and 1 is **2**. Here's a simple step-by-step breakdown: 1.

Jul 25, 2023 · Using GGML quantized models, let's say we are going to talk about 4bit. I see a lot of versions suffixed with either 0, 1, k_s or k_m. I understand that the difference is in the way of quantization that affect the final size of the quantized models but how does this effect quality of output and speed of inference?