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A little curiosity. A world of open source.
THE FIRST COLLECTIONThe Chinese-LLaMA-Alpaca project enhances the original LLaMA model for Chinese NLP by expanding its vocabulary, conducting secondary pre-training with Chinese corpora, and fine-tuning with instruction data. It offers instruction-tuned models, LoRA weights, training scripts, and quantization/deployment tools for local CPU/GPU execution, supporting various ecosystem tools.
Troy is a CLI tool for fine-tuning and preference-tuning LLMs locally on Apple Silicon Macs. Using MLX, it allows users to train models via a simple YAML config without cloud or CUDA requirements.
LlamaFactory is a Python framework for efficient fine-tuning of 100+ large language and multimodal models, offering zero-code CLI, a Gradio Web UI, LoRA/QLoRA, and multiple training algorithms.
PEFT is a library providing state-of-the-art Parameter-Efficient Fine-Tuning methods to adapt large pretrained models with minimal computational and storage costs.
Collection of simple PyTorch implementations of neural networks and deep learning papers with documented side-by-side explanations, covering transformers, GANs, diffusion models, RL, optimizers, and more.
