aimet
ludwig
| aimet | ludwig | |
|---|---|---|
| 2 | 3 | |
| 2,197 | 11,279 | |
| 1.6% | 0.6% | |
| 9.8 | 7.1 | |
| 8 days ago | 10 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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.
aimet
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I was looking for some great quantization open-source libraries that could actually be applied in production (both edge or cloud CPU/GPU). Do you know if I am missing any good libraries?
Qualcomm AIMET | Advanced quantization and compression techniques for trained neural network models
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Model/Tool to use on Jetson for efficient Quantization/Pruning
Qualcomm AIMET may help you
ludwig
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Show HN: Toolkit for LLM Fine-Tuning, Ablating and Testing
This is a great project, little bit similar to https://github.com/ludwig-ai/ludwig, but it includes testing capabilities and ablation.
questions regarding the LLM testing aspect: How extensive is the test coverage for LLM use cases, and what is the current state of this project area? Do you offer any guarantees, or is it considered an open-ended problem?
Would love to see more progress toward this area!
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Python projects with best practices on Github?
Two random examples I found from 30 seconds of googling: Here’s Netflix using it in their crisis management tool, and here’s Uber using it in their deep learning framework.
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Most Frequent 600 Coding Questions on LeetCode
They list themselves all over the internet as an "open source contributor" to Uber, which as far I can tell is based entirely on... reporting that there was an issue with a favicon. To me, it seems like they'll be cheating anybody who employs them based on this, ahem, "experience". And that feels like the tip of the iceberg.
What are some alternatives?
model-optimization - A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
ai-deadlines - :alarm_clock: AI conference deadline countdowns
qkeras - QKeras: a quantization deep learning library for Tensorflow Keras
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
tkDNN - Deep neural network library and toolkit to do high performace inference on NVIDIA jetson platforms
data-structures-and-algorithms - Resources that I used to crack some big tech & startups interviews
distiller - Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
nlp-recipes - Natural Language Processing Best Practices & Examples
open-lpr - Open Source and Free License Plate Recognition Software
mlnotify - 🔔 No need to keep checking your training - just one import line and you'll know the second it's done.
orion - Asynchronous Distributed Hyperparameter Optimization.
clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP