pytorch-lightning
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes. (by Lightning-AI)
playtorch
PlayTorch is a framework for rapidly creating mobile AI experiences. (by facebookresearch)
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| pytorch-lightning | playtorch | |
|---|---|---|
| 8 | 10 | |
| 26,797 | 818 | |
| 1.7% | - | |
| 9.9 | 0.0 | |
| 1 day ago | 6 months ago | |
| Python | MDX | |
| 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.
pytorch-lightning
Posts with mentions or reviews of pytorch-lightning.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-08.
- Lightning AI Studios – A persistent GPU cloud environment
-
Como empezar con inteligencia artificial?
https://see.stanford.edu/Course/CS229 https://lightning.ai/ https://www.youtube.com/watch?v=00s9ireCnCw&t=57s https://towardsdatascience.com/
-
Best practice for saving logits/activation values of model in PyTorch Lightning
I've been wondering on what is the recommended method of saving logits/activations using PyTorch Lightning. I've looked at Callbacks, Loggers and ModelHooks but none of the use-cases seem to be for this kind of activity (even if I were to create my own custom variants of each utility). The ModelCheckpoint Callback in its utility makes me feel like custom Callbacks would be the way to go but I'm not quite sure. This closed GitHub issue does address my issue to some extent.
- New to ML, which is easier to learn - Tensorflow or PyTorch?
- PyTorch Lightning – DL framework to train, deploy, and ship AI fast
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We just release a complete open-source solution for accelerating Stable Diffusion pretraining and fine-tuning!
Our codebase for the diffusion models builds heavily on OpenAI's ADM codebase , lucidrains, Stable Diffusion, Lightning and Hugging Face. Thanks for open-sourcing!
-
An elegant and strong PyTorch Trainer
For lightweight use, pytorch-lightning is too heavy, and its source code will be very difficult for beginners to read, at least for me.
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[D] Mixed Precision Training: Difference between BF16 and FP16
For the A100 GPU, theoretical performance is the same for FP16/BF16 and both rely on the same number of bits, meaning memory should be the same. However since it's quite newly added to PyTorch, performance seems to still be dependent on underlying operators used (pytorch lightning debugging in progress here).
playtorch
Posts with mentions or reviews of playtorch.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-26.
-
[D] Pytorch or TensorFlow for development and deployment?
First, PlayTorch is a thing. That could replace tflite for mobile.
- PlayTorch – Build your AI powered mobile prototypes in minutes
- ¿Data Science o Diseño Web?
- [D] Anyone tried using Apple’s Swift for Machine Learning
-
using a teachable machine model in react native
maybe this package can help you here
- Easy to use set of tools to create on-device ML demos on Android and iOS. Unlock the vast potential of AI innovations.
-
[D] Are you using PyTorch or TensorFlow going into 2022?
I'd say stick with PT for now! If you're interested in deployment, might wanna look into TF, but I'd use PyTorch Live to build a mobile application before you do that!
-
Introducing PyTorch Live!!
Learn more here - https://pytorch.org/live/
- PyTorch Live: an easy to use command line interface, a React Native package, and a React Native template to build, deploy, and share machine learning models
What are some alternatives?
When comparing pytorch-lightning and playtorch you can also consider the following projects:
lnd - Lightning Network Daemon ⚡️
equinox - Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
Eclair - A scala implementation of the Lightning Network.
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
mmdetection - OpenMMLab Detection Toolbox and Benchmark
lernapparat - Various Notebooks for Lernapparat.de
composer - Supercharge Your Model Training
functorch - functorch is JAX-like composable function transforms for PyTorch.
umbrel - A beautiful home server OS for self-hosting with an app store. Buy a pre-built Umbrel Home with umbrelOS, or install on a Raspberry Pi 4, Pi 5, any Ubuntu/Debian system, or a VPS.
ml5-library - Friendly machine learning for the web! 🤖
Keras - Deep Learning for humans
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
pytorch-lightning vs lnd
playtorch vs equinox
pytorch-lightning vs Eclair
playtorch vs pytorch-lightning
pytorch-lightning vs mmdetection
playtorch vs lernapparat
pytorch-lightning vs composer
playtorch vs functorch
pytorch-lightning vs umbrel
playtorch vs ml5-library
pytorch-lightning vs Keras
playtorch vs jax