language-model

Language Model Fine-tuning for Moby Dick

Collection of Basic Prompt Templates for Various Chat LLMs (Chat LLM 的基础提示模板集合)

Tree prompting: easy-to-use scikit-learn interface for improved prompting.

Language Model that makes you Laugh .

A guide about how to use GPTQ models with langchain

Finetune BLOOM

Training LLaMA language model with MMEngine! It supports LoRA fine-tuning!

This is a obsidian plugin to help with the creation of personal jsonl datasets for text generation models.

A production-ready, scalable multi-agent system built with LangGraph, featuring specialized agents for different tasks with best coding practices.

A re-implementation of the "Extracting Training Data from Large Language Models" paper by Carlini et al., 2020

Code for building self-expanding knowledge graphs with Outlines, vLLM, neo4j, and Modal.

Latxa: An Open Language Model and Evaluation Suite for Basque

This repository will guide you to create your Images via Stable Diffusion using a Smart Virtual Assistant like Google Assistant using Open AI's ChatGPT, Whisper. The entire solution is created using Python & Gradio.

A Word Level Transformer layer based on PyTorch and 🤗 Transformers.

Taught by AI genius Andrew NG, this course entails the cutting edge topics such as, How generative AI works including what it can and can't do, Common uses cases such as Reading, Writing, and Chatting, Life Cycle of GenAI projects, Advanced Technology options such as RAG, Fine tunning, and Pre-Training, Implications of GenAI on business & Society.

用于微调LLM的中文指令数据集

Generate README.md with GPT-3 few-shot learning

Pretraining and Finetuning Language Model

[ACL 2023] The code for our ACL'23 paper Cold-Start Data Selection for Few-shot Language Model Fine-tuning: A Prompt-Based Uncertainty Propagation Approach

MinimalGPT is a concise, adaptable, and streamlined code framework that encompasses the essential components necessary for the construction, training, inference, and fine-tuning of the GPT model. This framework is implemented exclusively using Keras and TensorFlow, ensuring compatibility and coherence within the broader deep learning ecosystem.