Discussing the article: "Integrate Your Own LLM into EA (Part 4): Training Your Own LLM with GPU"
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Check out the new article: Integrate Your Own LLM into EA (Part 4): Training Your Own LLM with GPU.
With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to their needs, deploy them locally, and then apply them to algorithmic trading. This series of articles will take a step-by-step approach to achieve this goal.
In the previous article, we briefly discussed how to create datasets for large language models and demonstrated how to train a language model using only a CPU with a simple example. However, we did not test the model because, in real terms, it was only a pre-trained model. In this article, we continue our discussion on model training, this time using GPUs to accelerate the process. It’s important to note that, as a demonstration example, this model is still not powerful enough, so we won’t cover model testing in this article. Testing will be addressed in subsequent articles.
We previously covered the setup of CUDA acceleration environments in the second part of this series. Now, we’ll focus on using AMD graphics cards to accelerate training, which serves as a supplement to that previous article. Currently, setting up an NVIDIA graphics card environment is relatively straightforward, while configuring an environment for AMD cards may present various challenges. In this article, we’ll provide solutions to common issues, allowing you to smoothly accelerate training for your own financial language model using AMD graphics cards. If you’re using NVIDIA graphics cards, don’t worry—the training methods are the same. As long as you’ve already set up the CUDA environment, you can follow the training instructions provided in this article without needing to focus on the specific configuration steps for AMD cards.
Are you ready to go?
Author: Yuqiang Pan