Mingmin from Aofeisi Quantum Bit | Public Account QbitAI It must be said that to enable more people to use large models, the tech community is indeed coming up with various tricks! Not open enough models? Some people are taking matters into their own hands to create free open-source versions. For example, the recently popular … Read more
Introduction This practical guide uses the 0.5B model of QWEN2.5 for fine-tuning on the Ruozhi Bar dataset. As we all know, there are many absurd questions in the Ruozhi Bar.Although these nonsensical questions may seem like forced ambiguity of Chinese semantics from a human perspective, they actually provide high-quality training data for the model to … Read more
When I first used Linux, the first thing I wanted to do was install the GPU version of TensorFlow. I found a great guide, but even considering that, I spent over 40 hours on the installation. In this article, I want to save you time and share my experience. Below you will find an updated … Read more
Installing TensorFlow on Windows Installing Python First, you need to install Python on your Windows system. It is recommended to use the official Python distribution, which is Anaconda, as it comes with many scientific computing libraries, such as numpy and scipy, which are also used in TensorFlow. You can download and install Anaconda from the … Read more
Click the above “Beginner Learning Vision” to select Star or Pin. Important content delivered promptly This article is transferred from | Computer Vision Alliance Overview tf.distribute.Strategy is a TensorFlow API used to distribute training across multiple GPUs, multiple machines, or TPUs. With this API, you can distribute existing models and training code with minimal code … Read more
TensorFlow programs can specify the device for each operation using the tf.device function. This device can be a local CPU or GPU, or it can be a remote server. TensorFlow assigns a name to each available device, and the tf.device function can specify the device for executing operations using the device’s name. For example, the … Read more
Introduction The main difference between the CPU version and the GPU version is the running speed; the GPU version runs faster. Therefore, if your computer’s graphics card supports CUDA, it is recommended to install the GPU version. The CPU version requires no additional preparation and can generally be installed on any computer without needing a … Read more
Click the “Beginner’s Guide to Vision” above, and choose to add “Star” or “Top“ Heavy content delivered promptly Why Use Multi-GPU Parallel Training In simple terms, there are two reasons: the first is that the model cannot fit on a single GPU, but can run completely on two or more GPUs (like the early AlexNet). … Read more
Click on the above “Beginner Learning Visuals” to select “Star” or “Pin” Important content delivered to you first Selected from | Medium Author | Aakash N S Contributors | Panda This article is the fourth in this series and will introduce how to train deep neural networks using PyTorch on a GPU. In previous tutorials, … Read more
Source: Read Chip Technology This article is approximately 4800 words, and it is recommended to read it in 10 minutes. This article introduces 9 tips for training neural networks using Pytorch. Image Source: unsplash.com/@dulgier In fact, your model may still be at the level of the Stone Age. You might still be training with 32-bit … Read more