modelstore
🏬 modelstore is a Python library that allows you to version, export, and save a machine learning model to your filesystem or a cloud storage provider. (by operatorai)
wandb
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production. (by wandb)
| modelstore | wandb | |
|---|---|---|
| 4 | 19 | |
| 379 | 9,366 | |
| 1.1% | 2.1% | |
| 5.9 | 9.9 | |
| 8 months ago | 2 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
modelstore
Posts with mentions or reviews of modelstore.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-07-01.
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An open source ML model registry called modelstore
A couple of years ago (during a lockdown!), I started working on modelstore - a Python library for managing trained machine learning models.
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lightweight model performance tracking?
The lightest open source option I'm aware of is https://github.com/operatorai/modelstore
- What us the best MLOps platform for 2022
- [D] using git or other tools to manage models
wandb
Posts with mentions or reviews of wandb.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-10-05.
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[Python] How do we lazyload a Python module? - analyzing LazyLoader from MLflow
One day I was hopping around a few popular ML libraries in Python, including MLflow. While glancing at its source code, one class attracted my interest, LazyLoader in __init__.py (well, this actually mirrors from the wandb project, but the original code has changed from what MLflow is using now, as you can see).
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Fine-Tune Llama 3.1 8B using QLORA
A Weights & Biases access token (Optional).
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10 Open Source Tools for Building MLOps Pipelines
Weights and Biases (W&B) ****is a tool for visualizing and tracking machine learning experiments. It supports major machine learning frameworks such as TensorFlow and PyTorch. Its key features include:
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A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
Weights & 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.
- Northlight makes Alan Wake 2 shine
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The last sentence of Lowes conveniently missing from OpenAI...
HuggingFace and wandb.ai (both competitors of OpenAI) both also have "do own research"
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Efficient way to tune a network by changing hyperparameters?
Wandb is the best! https://wandb.ai/
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[D] Monitoring production image models
To track stuff I've used wandb.ai in a company in the past, as someone else pointed out. Regarding metrics... This is really specific to your domain, and it is such a broad question. You could count color pixels, the distribution of intensity histograms, etc etc.
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How to use the colab notebook version of Dall-E mini and bypass the traffic limit - A guide
Step 1: The colab notebook uses wandb.ai, so you need to register for a wandb.ai account beforehand if you want to use the colab notebook. After registering you need to go to your homepage and copy the API key and paste/keep it somewhere.
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Roadmap for learning MLOps (for DevOps engineers)
I want to take a look at tools like https://wandb.ai/ and they would integrate into some of the pipelines I'm playing with.
What are some alternatives?
When comparing modelstore and wandb you can also consider the following projects:
onnxmltools - ONNXMLTools enables conversion of models to ONNX
tensorboard - TensorFlow's Visualization Toolkit
gato - Unofficial Gato: A Generalist Agent
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
guildai - Experiment tracking, ML developer tools
polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
pytorch-summary - Model summary in PyTorch similar to `model.summary()` in Keras
Tetris-deep-Q-learning-pytorch - Deep Q-learning for playing tetris game