Staying up-to-date with the latest LLM releases can be time-consuming, as it requires regularly following academic journals, conferences, industry publications, and social media accounts of experts in the NLP field. However, investing this time can significantly benefit your work in natural language processing.
Alternatively, seeking out a trusted source that curates a comprehensive list of new LLM releases can save you time and effort while still keeping you informed. This way, you can quickly and easily discover the latest advancements in the field without having to do the research yourself.
One useful resource for staying up-to-date with the latest large language models is the “Awesome-LLM” repository on GitHub. Created and maintained by Hannibal046, this repository contains comprehensive information on a wide range of LLMs, including their architecture, training data, and performance benchmarks.
GitHub Repo link — https://github.com/Hannibal046/Awesome-LLM
The repository is constantly updated with new LLM releases, making it a valuable resource for anyone working in the field of natural language processing. By accessing the information in the “Awesome-LLM” repository, you can easily discover new LLMs that might be relevant to your work and evaluate their potential usefulness.
This repository contains the following table of contents:
- Milestone Papers (The milestone papers list is helpful for exploring the history and state-of-the-art of LLM)
- Other Papers (Detailed list of papers in various subfields)
- LLM Leaderboard
– Pre-trained LLM
– Instruction finetuned LLM
– Aligned LLM
– Open sourced LLM
- LLM Training Frameworks (To train your own LLM)
- Open LLM
- Tools for deploying LLM (To deploy the LLM)
- Tutorials about LLM
- Courses about LLM
- Opinions about LLM
- Other Awesome Lists
- Other Useful Resources
The “Awesome-LLM” repository serves as a one-stop-shop for anyone interested in exploring the world of large language models. With its comprehensive table of contents, users can easily navigate through various sections that cover a wide range of topics, such as LLM milestone papers, training frameworks, deployment tools, tutorials, courses, opinions, and other resources.
One of the most significant benefits of this repository is that it saves users a lot of time and effort by curating high-quality resources in one place. Instead of spending hours searching for reliable sources or blogs to learn about LLM, users can dive straight into the repository to access a plethora of information. Whether one is looking to create their own LLM, deploy it, or understand the theoretical concepts behind LLM, this repository has everything needed to get started.