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Top 13 model-compression 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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Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
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InfluxDB
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Pretrained-Language-Model
Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.
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Torch-Pruning
[CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs
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model-optimization
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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archai
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
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only_train_once
OTOv1-v3, NeurIPS, ICLR, TMLR, DNN Training, Compression, Structured Pruning, Erasing Operators, CNN, Diffusion, LLM
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UPop
[ICML 2023] UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers.
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Awesome-Pruning-at-Initialization
[IJCAI'22 Survey] Recent Advances on Neural Network Pruning at Initialization.
Project mention: Does anyone know a downloadable chatgpt model that supports conversation in Albanian? | /r/Programimi | 2023-05-16
Project mention: [P] Help: I want to compress EfficientnetV2 using pruning. | /r/MachineLearning | 2023-06-28I also tried structured pruning from https://github.com/VainF/Torch-Pruning, as they report EfficientNetV2 to be "prunable", but got much worse results. However, the advantage of this approach is that it keeps the model dense, and you can get a real speed-up with common GPUs, while unstructured pruning sparsifies the model and you need hardware that can exploit such sparsity.
Project mention: DeepCache: Accelerating Diffusion Models for Free | news.ycombinator.com | 2023-12-05
Using the currently popular gptq the 3bit quantization hurts performance much more than 4bit, but there's also awq (https://github.com/mit-han-lab/llm-awq) and squishllm (https://github.com/SqueezeAILab/SqueezeLLM) which are able to manage 3bit without as much performance drop - I hope to see them used more commonly.
Project mention: Show HN: Compress vision-language and unimodal AI models by structured pruning | news.ycombinator.com | 2023-07-31
model-compression related posts
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Llama33B vs Falcon40B vs MPT30B
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Has anyone tried out Squeezellm?
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[P] Help: I want to compress EfficientnetV2 using pruning.
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SqueezeLLM: Dense-and-Sparse Quantization
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New quantization method SqueezeLLM allows for loseless compression for 3-bit and outperforms GPTQ and AWQ in both 3-bit and 4-bit. Quantized Vicuna and LLaMA models have been released.
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Requesting help with Custom Layers (Layer Subclassing) - Model fit builds the model again! [Keras]
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Researchers From China Introduce Vision GNN (ViG): A Graph Neural Network For Computer Vision Systems
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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 model-compression projects? This list will help you:
Project | Stars | |
---|---|---|
1 | nni | 13,742 |
2 | Efficient-AI-Backbones | 3,804 |
3 | Pretrained-Language-Model | 2,960 |
4 | Awesome-Knowledge-Distillation | 2,402 |
5 | Torch-Pruning | 2,307 |
6 | model-optimization | 1,470 |
7 | DeepCache | 603 |
8 | SqueezeLLM | 569 |
9 | archai | 455 |
10 | only_train_once | 261 |
11 | KVQuant | 190 |
12 | UPop | 83 |
13 | Awesome-Pruning-at-Initialization | 55 |
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