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Chat with your favourite LLaMA models in a native macOS app
This project is a quantized fine-tuning framework for large language models. It implements a low-rank adaptation library and a four-bit quantizer to reduce the GPU memory requirements needed to train large models. The framework utilizes four-bit quantization and low-rank adapters to enable model training on consumer-grade hardware. It further reduces the memory footprint through double quantization and a paged optimizer that offloads states to system RAM. The system supports distributed training across multiple GPUs to handle larger parameter scales and includes utilities for custom dataset
Open Academic Research on Improving LLaMA to SOTA LLM
ChatGPT爆火，开启了通往AGI的关键一步，本项目旨在汇总那些ChatGPT的开源平替们，包括文本大模型、多模态大模型等，为大家提供一些便利
ChatGLM-6B-Slim：裁减掉20K图片Token的ChatGLM-6B，完全一样的性能，占用更小的显存。
The main features of silverriver/chatglm-6b-slim are: LLM Training and Optimization, Natural Language Processing.
Projects with overlapping indexed features include: artidoro/qlora — This project is a quantized fine-tuning framework for large language models. It implements a low-rank adaptation… facico/chinese-vicuna — Chinese-Vicuna is a Chinese large language model and instruction-following AI based on the LLaMA architecture. It is… aethercortex/llama-x — Open Academic Research on Improving LLaMA to SOTA LLM. alexrozanski/llamachat — Chat with your favourite LLaMA models in a native macOS app. chenking2020/findthechatgpter — ChatGPT爆火，开启了通往AGI的关键一步，本项目旨在汇总那些ChatGPT的开源平替们，包括文本大模型、多模态大模型等，为大家提供一些便利. jayzhang42/federatedgpt-shepherd — Shepherd: A foundational framework enabling federated instruction tuning for large language models.