gabrevaya

gabrevaya's Stars

• ggerganov/llama.cpp

  LLM inference in C/C++

  Language:C++65.9k5503.8k9.5k

• abi/screenshot-to-code

  Drop in a screenshot and convert it to clean code (HTML/Tailwind/React/Vue)

  Language:Python56.4k3292996.9k

• continuedev/continue

  ⏩ Continue is the leading open-source AI code assistant. You can connect any models and any context to build custom autocomplete and chat experiences inside VS Code and JetBrains

  Language:TypeScript17.7k891.5k1.4k

• KindXiaoming/pykan

  Kolmogorov Arnold Networks

  Language:Jupyter Notebook14.8k1103911.3k

• facebookresearch/seamless_communication

  Foundational Models for State-of-the-Art Speech and Text Translation

  Language:Jupyter Notebook10.8k1403501.1k

• linto-ai/whisper-timestamped

  Multilingual Automatic Speech Recognition with word-level timestamps and confidence

  Language:Python1.9k30146153

• time-series-foundation-models/lag-llama

  Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

  Language:Python1.2k3298147

• Ceyron/machine-learning-and-simulation

  All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.com/channel/UCh0P7KwJhuQ4vrzc3IRuw4Q)

  Language:Jupyter Notebook8402510177

• SpeedyWeather/SpeedyWeather.jl

  Play atmospheric modelling like it's LEGO.

  Language:Julia4361414927

• svilupp/PromptingTools.jl

  Streamline your life using PromptingTools.jl, the Julia package that simplifies interacting with large language models.

  Language:Julia12063713

• mitmath/JuliaComputation

  Repository for Common Ground C25

  Language:Julia899313

• yobibyte/compressor

  Because we don't have enough time to read everything

  Language:Python834410

• svilupp/awesome-generative-ai-meets-julia-language

  Comprehensive guide to generative AI projects and resources in Julia.

  66603

• svilupp/AIHelpMe.jl

  Harnessing Julia's Rich Documentation for Tailored AI-Assisted Coding Guidance

  Language:Julia364145

• payel79/PEDS

  Language:Julia30409

• vboussange/WSLJuliaWorkshop2023

  Practical introduction to Julia for modelling and data analysis in biodiversity and earth sciences

  Language:Jupyter Notebook26216

• MirageML/mirageml_pip

  Pip Package for MirageML

  Language:Python25372

• FedeClaudi/HelpGPT.jl

  Let the AI fix your mistakes.

  Language:Julia18220

• gon-uri/detach_rocket

  This repository contains the implementation of Sequential Feature Detachment (SFD) for feature selection and its application to Detach-ROCKET for time series classification.

  Language:Python17310

• brendanjohnharris/TimeseriesTools.jl

  A convenient package for working with time series (time-indexed arrays)

  Language:Julia16270

• zavalab/PlasmoData.jl

  Language:Julia13192

• white-alistair/Stabilized-Neural-Differential-Equations

  Code and experiments for the NeurIPS 2023 paper Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints

  Language:Julia11201

• TUM-PIK-ESM/TUM-Dynamics-Lecture

  Lectures, code and material for the Modelling and Machine Learning of Dynamical Systems in Julia lecture at Technical University Munich

  Language:Jupyter Notebook8200

• vboussange/PiecewiseInference.jl

  Inverse modelling framework for dynamical systems characterised by complex dynamics.

  Language:Julia8150

• brendanjohnharris/Foresight.jl

  A Makie theme

  Language:Julia6120

• JuliaHealth/NeuroAnalyzer.jl

  Julia toolbox for analyzing neurophysiological data

  Language:Julia5201

• maximilian-gelbrecht/NODEData.jl

  Small helper package that provides a struct for sequence learning with Neural ODEs.

  Language:Julia4101

• maximilian-gelbrecht/NPDEChaos

  This is the source code of the Neural Partial Differential Equations for Chaotic Processes Paper.

  Language:Julia4100

• maximilian-gelbrecht/ChaoticNDETools.jl

  A collection of tools, helper functions and layers to assist working with chaotic Neural Differential Equation in Julia

  Language:Julia2102

• TUM-PIK-ESM/ML-DS-Workshop-23

  Machine Learning for Dynamical Systems Workshop February 23 at TUM

  Language:Jupyter Notebook21