Explore >> Select a destination
|
You are here 
|
www.datadoghq.com | ||
| | | | |
bair.berkeley.edu
|
|
| | | | | [AI summary] The article introduces Koala, a dialogue model trained by fine-tuning Meta's LLaMA on dialogue data from the web, with a focus on interactions with large closed-source models like ChatGPT. The model's performance is compared to ChatGPT and Stanford's Alpaca, showing competitive results. The paper emphasizes the importance of high-quality training data for smaller models and highlights the potential for open-source models to match the performance of closed-source ones. However, it also acknowledges the limitations and safety concerns of Koala, including potential for misinformation and biases, and emphasizes its research prototype status for academic use. | |
| | | | |
www.solo.io
|
|
| | | | | Learn how the Omni vision unifies traffic, security, and observability control across cloud-native systems with Gloo Mesh and Gloo Gateway. | |
| | | | |
blog.adnansiddiqi.me
|
|
| | | | | Learn the basics of Large Language Models (LLMs) in this introduction to GenAI series. Discover how LLMs work, their architecture, and practical applications like customer support, content creation, and software development. | |
| | | | |
blog.paperspace.com
|
|
| | | Follow this tutorial to learn what attention in deep learning is, and why attention is so important in image classification tasks. We then follow up with a demo on implementing attention from scratch with VGG. | ||
