truemanstock's starred repositories
Dreambooth-Stable-Diffusion
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
LLaMA-Adapter
[ICLR 2024] Fine-tuning LLaMA to follow Instructions within 1 Hour and 1.2M Parameters
alpha-zero-general
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
Dreambooth-Stable-Diffusion
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) by way of Textual Inversion (https://arxiv.org/abs/2208.01618) for Stable Diffusion (https://arxiv.org/abs/2112.10752). Tweaks focused on training faces, objects, and styles.
clip-interrogator
Image to prompt with BLIP and CLIP
muzero-general
MuZero
word2vec
This tool provides an efficient implementation of the continuous bag-of-words and skip-gram architectures for computing vector representations of words. These representations can be subsequently used in many natural language processing applications and for further research.
DreamArtist-stable-diffusion
stable diffusion webui with contrastive prompt tuning
DreamArtist-sd-webui-extension
DreamArtist for Stable-Diffusion-webui extension
awesome-monte-carlo-tree-search-papers
A curated list of Monte Carlo tree search papers with implementations.
awesome-image-denoising-state-of-the-art
awesome image and video denoising, state of the art networks
Tabular-LLM
本项目旨在收集开源的表格智能任务数据集(比如表格问答、表格-文本生成等),将原始数据整理为指令微调格式的数据并微调LLM,进而增强LLM对于表格数据的理解,最终构建出专门面向表格智能任务的大型语言模型。
simple-videochat-webrtc
Video chat between 2 people using simple-peer
OpenAI-CLIP-Feature
An easy to use, user-friendly and efficient code for extracting OpenAI CLIP (Global/Grid) features from image and text respectively.
Book-of-MLM
《多模态大模型:新一代人工智能技术范式》作者:刘阳,林倞
langchain-ask-pdf-local
An AI-app that allows you to upload a PDF and ask questions about it. It uses StableVicuna 13B and runs locally.
chinese-StableVicuna
全球首个StableVicuna中文优化版。
DenoisingAE
Denoising autoencoders for anomaly detection in medical imaging
Few-Shot-Regression
code for the paper "Few-Shot Regression via Learning Sparsifying Basis Functions
LLaMA-Adapter-2
Fine-tuning LLaMA to follow Instructions within 1 Hour and 1.2M Parameters