zero_nlp

Why we included this project

Anyone who has tried to train a Chinese NLP model from scratch knows how much of the work is in the data pipeline, not the model code. This project collects complete, runnable recipes for a wide range of architectures, including GPT-2, CLIP, ChatGLM, LLaMA, GPT-NeoX, Dolly, and image-captioning models, each walking from raw data cleaning through preprocessing, training, and sometimes deployment, with flow diagrams that make the steps easy to follow. It is a good fit for teams stuck with consumer GPUs, because it shows how to chain multiple cards for training and inference, and includes practical tools like vocabulary trimming and expansion. Since everything builds on PyTorch and the transformers library, developers already comfortable with those tools can copy the patterns straight into their own work.