Running the example script llm-compressor/examples/quantization_w4a4_fp4/llama3_example.py results in a runtime error. Full traceback is included below.

🚀公式 SINQ リポジトリへようこそ! SINQ (Sinkhorn-Normalized Quantization)は、大規模言語モデルの精度をほぼそのまま維持しながら、モデルを縮小するように設計された、新しい高速で高品質な量子化手法です。 🔥 SINQ量子化の美学 ― 誤差を制する者が、AIを制す ...

Abstract: The quantization technique of neural networks can achieve a compressed representation of models by reducing weights and activations data bitwidth, accelerating the inference process, and ...

Hi, thanks for the amazing work. I need some help understanding how to choose the layers for specific models, especially those without examples. I am currently looking at Qwen3-32b, which I see only ...

It’s a counterintuitive result that you might need to add noise to an input signal to get the full benefits from oversampling in analog to digital conversion. [Paul Allen] steps us through a simple ...

Abstract: Generative neural image compression supports data representation at extremely low bitrate, synthesizing details at the client and consistently producing ...