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Top 23 hyperparameter-tuning Open-Source Projects
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nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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wandb
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
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InfluxDB
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skypilot
SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface.
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determined
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
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coursera-deep-learning-specialization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
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rl-baselines3-zoo
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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vizier
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
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rl-baselines-zoo
A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
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onepanel
The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
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OCTIS
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)
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syne-tune
Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.
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Hypernets
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
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DPL
[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks. (by releaunifreiburg)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Project mention: A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev | dev.to | 2024-02-05Weights & Biases — The developer-first MLOps platform. Build better models faster with experiment tracking, dataset versioning, and model management. Free tier for personal projects only, with 100 GB of storage included.
Project mention: Ask HN: Most efficient way to fine-tune an LLM in 2024? | news.ycombinator.com | 2024-04-04
17. Determined AI | Github | tutorial
Project mention: coursera-deep-learning-specialization: NEW Courses - star count:2327.0 | /r/algoprojects | 2023-11-21
Project mention: Can't solve MountainCar-v0 with A2C algorithm (stable-baselines3) | /r/reinforcementlearning | 2023-06-27I'm trying to solve MountainCar-v0 enviroment from gymnasium with the A2C algorithm and the agent doesn't find a solution. I checked this so I added import stable_baselines3.common.sb2_compat.rmsprop_tf_like as RMSpropTFLike. Also checked the rl-baselines3-zoo for the hyperparameter tuning. So my code is:
Project mention: [P] Introducing PPO and Rainbow DQN to our super fast evolutionary HPO reinforcement learning framework | /r/MachineLearning | 2023-10-15
Project mention: tune: An abstraction layer for parameter tuning | /r/coolgithubprojects | 2023-05-07
Project mention: How Do I Perform Hyperparameter Optimization for a Non-Toy Dataset in R Using mlr3hyperband? | /r/rprogramming | 2023-05-07that I want to use to train an XGBoost predictive model. Now under the example given by the mlr3hyperband documentation, the steps to perform hyperparameter optimization are as follows:
Project mention: Power Laws for Hyperparameter Optimization [LLM application] | /r/deeplearning | 2023-06-14
hyperparameter-tuning related posts
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SGLang: Fast and Expressive LLM Inference with RadixAttention for 5x Throughput
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Serving Your Private Code Llama-70B with API, Chat, and VSCode Access
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A new old kind of R&D lab
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New Recipe: Serving Llama-2 with VLLM's OpenAI-Compatible API Server
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Train Your Own Vicuna on Llama-2
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Run Llama2 in your cloud privately
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SkyPilot: Run LLMs, AI, and Batch jobs on any cloud
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A note from our sponsor - InfluxDB
www.influxdata.com | 2 May 2024
Index
What are some of the best open-source hyperparameter-tuning projects? This list will help you:
Project | Stars | |
---|---|---|
1 | nni | 13,742 |
2 | wandb | 8,211 |
3 | auto-sklearn | 7,403 |
4 | skypilot | 5,636 |
5 | determined | 2,861 |
6 | coursera-deep-learning-specialization | 2,693 |
7 | rl-baselines3-zoo | 1,786 |
8 | vizier | 1,173 |
9 | rl-baselines-zoo | 1,106 |
10 | SMAC3 | 1,008 |
11 | evalml | 712 |
12 | onepanel | 696 |
13 | OCTIS | 685 |
14 | AgileRL | 493 |
15 | syne-tune | 363 |
16 | mango | 310 |
17 | Renate | 264 |
18 | Hypernets | 261 |
19 | sentence-classification | 235 |
20 | MGO | 71 |
21 | tune | 33 |
22 | mlr3hyperband | 18 |
23 | DPL | 11 |
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