Awesome-LLM is a curated list maintained by Hannibal046, aimed at bringing together various resources in the field of large language models (LLMs). The list mainly includes papers related to LLMs, especially research related to ChatGPT, and also covers LLM training frameworks, deployment tools, courses and tutorials, as well as all publicly available LLM checkpoints and APIs.
Purpose: To serve as a collection of learning and research resources in the LLM field, helping users quickly find key papers, frameworks, tools, and models.
Main capabilities:
- Provides a list of LLM milestone papers to help understand the history of the field's development.
- Includes other related papers, covering multiple subfields.
- Provides LLM leaderboards, such as Chatbot Arena Leaderboard, Open LLM Leaderboard, LiveBench, etc.
- Lists open-source LLM models, such as the DeepSeek, Qwen, Llama, OPT, Grok, and other series.
- Provides LLM data-related resources, such as LLMDataHub, IBM data-prep-kit, etc.
- Provides LLM evaluation tools, such as lm-evaluation-harness, lighteval, HELM, etc.
- Lists LLM training frameworks, such as DeepSpeed, Megatron-LM, torchtitan, Colossal-AI, etc.
- Provides LLM inference-related resources (reference links are mentioned on the page).
- Lists LLM applications, tutorials and courses, books, and thoughts about LLMs.
- Includes links to curated lists in multiple subfields, such as hallucination detection, prompt engineering, chain of thought, instruction tuning, model editing, safety, compression, healthcare, inference optimization, etc.
How to use: Users can access the list through the GitHub repository, browse the various sections and links, and obtain the resources they need. The list itself does not provide code or installation commands, but serves as a resource index.
Applicable scenarios: Suitable for researchers, developers, students, and people interested in LLMs, for finding reference materials when learning, researching, and developing LLM-related projects.
Limitations: The list is only a collection of resources and does not provide specific functions or services; some links may point to external resources, whose availability and content are maintained by third parties. The list does not provide fee, pricing, or platform information.
