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Introduction Fine-tuning large language models for code generation typically requires significant computing power. Many popular models, such as Code LLaMA or CodeT5, demand high-performance GPUs like NVIDIA A100, making them less accessible for most users. However, by leveraging LoRA (Low-Rank Adaptation) and quantization techniques with...
In this blog post, we will demonstrate how to perform custom training using the AWS Training Job service with xg-boost on a dataset. We will create our training job in four straightforward steps, enabling us to implement the entire process. By the end of this blog, you will be equipped to apply this technique, including preprocessing...
Written by Tushar Raj Verma & Abhishek Kumar Upadhyay Deep Convolutional Neural Networks have become the state of the art methods for image classification tasks. However, one of the biggest challenges is that they require a lot of labeled data to train the model. In many applications, collecting this much data is sometimes not...
