Smol Community
AI & ML interests
The SmolTuners group is a community dedicated to the development of small-scale Large Language Models (LLMs) using consumer-grade GPUs.
Recent Activity
discord community is here https://discord.gg/4cNKuTZ3
SmolTuners
The SmolTuners group is a community dedicated to the development of small-scale Large Language Models (LLMs) using consumer-grade GPUs. This initiative focuses on making advancements in machine learning accessible to those who do not have access to high-end, enterprise-level hardware. By leveraging consumer GPUs, members of SmolTuners aim to explore and implement techniques such as quantization and model parallelism to train, fine-tune, and run LLMs efficiently on hardware like the NVIDIA GeForce GTX series or newer models like the RTX series.
Group activities
- Experimentation with quantization:
Techniques like 2-bit quantization to reduce the memory footprint of LLMs, enabling them to fit into the limited RAM of consumer GPUs. This is supported by projects like llmtools by the Kuleshov group, which allows for finetuning LLMs on consumer GPUs with low precision like 2 bits. Model Parallelism: Utilizing methods to distribute model layers across multiple GPUs or even within a single GPU to manage larger models. This includes naive model parallelism, where different parts of the model are handled by different GPUs sequentially, which is particularly useful when training or running models that exceed the capacity of a single GPU.
- Community-driven development:
Sharing knowledge, code, and techniques through platforms like GitHub, where members might contribute to or use libraries like MiniLLM for running modern LLMs on consumer-grade GPUs. This project supports multiple LLMs at various sizes, making it viable for consumer hardware.
- Educational resources
Providing guides and tutorials on how to set up and run LLMs on personal computers, including how to deal with the challenges of limited hardware resources, such as using libraries like llama.cpp for offloading parts of the model to the GPU.
- Innovative use of software:
Employing open-source tools and frameworks that are optimized for lower resource environments, thus fostering innovation in AI research and application development among hobbyists, students, and small-scale researchers.
This group embodies the spirit of democratizing AI technology, making the complex process of training or using LLMs more approachable for those outside of well-funded research environments or large enterprises.
If you have any question feel free to open an discussion or ping me on x.com/s3nhs3nh