fritol's Stars
ollama/ollama
Get up and running with Llama 3.2, Mistral, Gemma 2, and other large language models.
mlabonne/llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Mikubill/sd-webui-controlnet
WebUI extension for ControlNet
state-spaces/mamba
Mamba SSM architecture
InstantID/InstantID
InstantID : Zero-shot Identity-Preserving Generation in Seconds 🔥
TencentARC/PhotoMaker
PhotoMaker [CVPR 2024]
NielsRogge/Transformers-Tutorials
This repository contains demos I made with the Transformers library by HuggingFace.
LiheYoung/Depth-Anything
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
vikhyat/moondream
tiny vision language model
microsoft/LLMLingua
To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.
robertmartin8/PyPortfolioOpt
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
borisbanushev/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
Codium-ai/AlphaCodium
Official implementation for the paper: "Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering""
bowang-lab/MedSAM
Segment Anything in Medical Images
bclavie/RAGatouille
Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.
Gourieff/sd-webui-reactor
Fast and Simple Face Swap Extension for StableDiffusion WebUI (A1111 SD WebUI, SD WebUI Forge, SD.Next, Cagliostro)
lucidrains/self-rewarding-lm-pytorch
Implementation of the training framework proposed in Self-Rewarding Language Model, from MetaAI
lxtGH/OMG-Seg
OMG-LLaVA and OMG-Seg codebase [CVPR-24 and NeurIPS-24]
Vaibhavs10/open-tts-tracker
ProjectNUWA/DragNUWA
chaojie/ComfyUI-DragNUWA
pratyushasharma/laser
The Truth Is In There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
yromano/cqr
Conformalized Quantile Regression
KillianLucas/aifs
Local semantic search. Stupidly simple.
VinodSangare/gnidart
pererossello/espectrograma
Doriandarko/Moondream1-streamlit
hsdevelops/cron-telebot
A telegram bot that schedules recurring messages
Cnernc/OptimalLinearSignal
This repository contains the implementation of an unsupervised machine learning model designed to optimize Profit and Loss (PnL) in quantitative finance. This model utilizes linear signals constructed from exogenous variables to maximize the Sharpe ratio.
thevickypedia/telegram-webhook
Telegram bot implementation using webhook