翻译比较直白和粗暴，意会即可。 这篇文章《A White Paper on Neural Network Quantization》是来自高通研究院，和之前谷歌的那篇文章名字有点像但是内容不一样。《Quantizing deep convolutional networks for efficient inference: A whitepaper》谷歌这篇文章是18年出的，大概讲了一下自家 ...

IT之家 9 月 15 日消息，科技媒体 marktechpost 昨日（9 月 14 日）发布博文， 报道称英伟达开源了 Nemotron-Mini-4B-Instruct AI 模型，标志着该公司在 AI 领域创新又一新篇章。

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AWQ方法已经在AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration论文中引入。通过AWQ，您可以以4位精度运行模型，同时保留其原始性能（即没有性能降级），并具有比下面介绍的其他量化方法更出色的吞吐量 - 达到与纯float16推理相似的吞吐量。

Nvidia Open Sources Nemotron-Mini-4B-Instruct: A 4,096 Token Capacity Small Language Model Designed for Roleplaying, Function Calling, and Efficient On-Device Deployment with 32 Attention Heads and ...

If you are looking to run LLAMA 3.1 70B locally this guide provides more insight into the GPU setups you should consider to ...

Keysight Technologies, Inc. has unveiled Quantum Circuit Simulation (Quantum Ckt Sim), an innovative circuit design ...

Learn how to optimize large language models (LLMs) using TensorRT-LLM for faster and more efficient inference on NVIDIA GPUs.

Keysight worked with Google Quantum AI on its new quantum circuit simulation solution that features frequency-domain flux ...

What's the best model to use for an enteprise AI workflow? That's a question that Martian model router will answer ...