Common Pitfalls in PyTorch

Common Pitfalls in PyTorch

Click the “CVer” above to select “Star” or “Pin”. Heavyweight content delivered at the first time. Author: Bi Ji Ji https://zhuanlan.zhihu.com/p/59271905 This article is authorized, and no secondary reproduction is allowed without permission. 1. The Differences Between nn.Module.cuda() and Tensor.cuda() Both the cuda() function can achieve memory migration from CPU to GPU for models and … Read more

Running Deekseek-R1 Distillation Model with Llama Edge

Running Deekseek-R1 Distillation Model with Llama Edge

DeepSeek-R1 uses reinforcement learning to significantly enhance the model’s inference capabilities. In tasks such as mathematics, coding, and natural language reasoning, its performance rivals that of OpenAI’s official version o1.The small model distilled from DeepSeek-R1 effectively inherits the reasoning patterns learned by the large model.This article primarily tests DeepSeek-R1-Distill-Llama-8B-GGUF using Llama Edge. Welcome to experiment … Read more

DeepSeek: Unraveling the AGI Black Box

DeepSeek: Unraveling the AGI Black Box

As tech giants erect parameter monuments in the desert of computing power, a squad of engineers adorned with dynamic routing badges is cutting open the metal abdomen of large models with algorithm welding guns. The latest leaked battle map from the DeepSeek laboratory shows that their open-source model is rewriting the underlying game theory of … Read more

Faster R-CNN Model and Deep Learning Environment Setup

Faster R-CNN Model and Deep Learning Environment Setup

1. Faster R-CNN Model The R-CNN series networks are the most classic networks in the field of object detection, and their model update ideas are easy to understand. The object detection process is divided into three stages: candidate box generation, feature extraction, classification, and regression. R-CNN is a detection network assembled from many modules, where … Read more