OpenMOSS / MOSS-Image
Official repository for MOSS-Image, a 5B-parameter base DiT model with high-quality text rendering, layout generation, and efficient fine-tuning.
OpenMOSS / MOSS-Image
jingyaogong / minimind
🧠 Train a 64M-parameter LLM from scratch in just 2h!
FareedKhan-dev / kimi-k3-in-c
A 2.78-trillion-parameter Kimi K3 running inference on a single CPU in 8.24 GB of RAM. Portable C99: no BLAS, no framework, no GPU.
huggingface / peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
NaiveAI-Labs / Naive-N0.5-Flash
Naive-N0.5-Flash is an open-weight 309B MoE model with 15.5B active parameters, built for coding and AI R&D.
canberk7 / ema-lightning
Tiny, fast and accurate Turkish text-to-speech. 8.6M parameters, 0.92% WER on Freya-TR-Eval, first audio in ~4 ms and 1,300× real time on one GPU. Streams audio, batches many callers on one GPU, and runs offline on a GPU or CPU.
ray-project / ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
open-edge-platform / anomalib
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
modelscope / ms-swift
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.8, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM5.3, Gemma4, Llava, Phi4, ...) (AAAI 2025).
optuna / optuna
A hyperparameter optimization framework
XingChen-AGI / Xing4.0-29B-Intent
Xing4.0-29B-Intent - schema-guided intent recognition and structured information extraction (intent and slot filling, entity, relation and event extraction). A 29B MoE with 4B activated parameters, Apache-2.0.
mediacutlet / pocket-tank
A 14M-parameter LLM keeps a virtual fish tank alive on an $8 ESP32-S3 — distilled from a 26B teacher into 7.56 MB, no network.
skypilot-org / skypilot
The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.
jingyaogong / minimind-v
👀 Train a 65M-parameter VLM from scratch in just 2h!
NaiboWang / EasySpider
A visual no-code/code-free web crawler/spider易采集：一个可视化浏览器自动化测试/数据采集/网页爬虫软件，可以无代码图形化的设计和执行爬虫任务。别名：ServiceWrapper面向Web应用的智能化服务封装系统。
deepspeedai / DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
crabtalk / bezel
A SwiftUI-lean GPUI component library, style flows through the environment, never through parameters.
Birfy / agentdescent
Gradient descent, but the parameters are agents — a parallel, asynchronous framework for self-evolving agents (skills, prompts, harnesses). Diffs are the gradients; the aggregator is the optimizer.
Andyyyy64 / whichllm
Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly.
joshpuckett / dialkit
A library to help you dial in interface parameters of any kind
Zihan-Su / Self_Gradient_Forcing_Plus
Autoregressive video generation with decoupled context-writing and denoising parameters, enabling up to 24-hour generation from 5s training windows.
Alamofire / Alamofire
Swift library for HTTP networking built on URLSession, offering chainable requests, parameter encoding, and response validation.
autogluon / autogluon
Fast and Accurate ML in 3 Lines of Code
casadi / casadi
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript
gempy-project / gempy
GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to address parameter and model uncertainties.
potatobeanradio / circuitRF
Full featured, cross-platform RF circuit + electromagnetic simulator. DC, S-parameters, harmonic balance, loadpull, envelope. Also supports 2D and 3D layout and design and electromagnetic MoM, FEM, FDTD + thermal FEM.
nasa / cea
Computes chemical equilibrium compositions of mixtures by free-energy minimization, plus thermodynamic and transport properties of the products.
wandb / wandb
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
47ng / nuqs
Type-safe search params state manager for React frameworks - Like useState, but stored in the URL query string.
nteract / papermill
📚 Parameterize, execute, and analyze notebooks
microsoft / FLAML
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
polyaxon / polyaxon
AI Infra / AI Orchestration / AI Control Plane
DLR-RM / rl-baselines3-zoo
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
sqliteai / warp
Run the full 2.78-trillion-parameter Kimi K3 model, DeepSeek V4.1 Flash or GLM-5.3-Flash beyond available RAM by streaming activated weights directly from NVMe. A dependency-free, embeddable C inference engine.
JuliaAI / MLJ.jl
A Julia machine learning framework
jothepro / doxygen-awesome-css
A customizable CSS theme that modernizes the HTML output of Doxygen documentation without changing its layout.
DBraun / DawDreamer
Digital Audio Workstation with Python; VST instruments/effects, parameter automation, FAUST, JAX, Warp Markers, and JUCE processors
sahilmahendrakar / paradee
An 8M-parameter English text-to-speech model distilled from Kokoro-82M. 9 MB, runs 18x real time on one CPU thread.
hyperopt / hyperopt
Distributed Asynchronous Hyperparameter Optimization in Python
Angel-ML / angel
A Flexible and Powerful Parameter Server for large-scale machine learning
openai / parameter-golf
Train the smallest LM you can that fits in 16MB. Best model wins!
meta-recsys / generative-recommenders
Repository hosting code for "Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations" (https://arxiv.org/abs/2402.17152).
bUnit-dev / bUnit
bUnit is a testing library for Blazor components that make tests look, feel, and runs like regular unit tests. bUnit makes it easy to render and control a component under test’s life-cycle, pass parameter and inject services into it, trigger event handlers, and verify the rendered markup from the component using a built-in semantic HTML comparer.
lmfit / lmfit-py
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize, and with many additional classes and methods for curve fitting.
hhoppe / Mesh-processing-library
C++ libraries and programs demonstrating mesh processing research published in ACM SIGGRAPH (1992-2003)
simpeg / simpeg
Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.
andrisgauracs / needle-2-esp32
A 45M-parameter LLM: needle 2 running fully offline on an ESP32-S3, turning plain-English requests into guaranteed-valid JSON tool calls.
vukrosic / glm-5.3-flash-from-scratch
A 25.7M-parameter GLM-5.3-Flash-inspired model trained from scratch and improved with executable-reward RL.
harrrshall / barunlm-35m
BarunLM-35M: a parameter-efficient 35M base language model trained on 5.7B tokens
mljar / mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
kubeflow / katib
Automated Machine Learning on Kubernetes
mlr-org / mlr
Machine Learning in R
google / vizier
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
autonomio / talos
Hyperparameter Experiments with TensorFlow and Keras
automl / SMAC3
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
AgileRL / AgileRL
The complete post-training stack for LLMs, plus RL for any problem. SFT, DPO and multi-turn agentic RL, with evolutionary hyperparameter optimization built in.
sbi-dev / sbi
sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you need fine-grained control or an easy-to-use interface, sbi has you covered.
optuna / optuna-examples
Examples for https://github.com/optuna/optuna
optuna / optuna-dashboard
Real-time Web Dashboard for Optuna.
perpetual-ml / perpetual
Perpetual is a high-performance gradient boosting machine. It delivers optimal accuracy in a single run without complex tuning through a simple budget parameter. It features out-of-the-box support for causal ML, continual learning, native calibration, and robust drift monitoring, along with Rust core and zero-copy bindings for Python and R