nvitop
tmu
nvitop | tmu | |
---|---|---|
5 | 5 | |
3,965 | 109 | |
- | 2.8% | |
7.3 | 9.2 | |
12 days ago | about 1 month ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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.
nvitop
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Nvtop: Linux Task Monitor for Nvidia, AMD and Intel GPUs
That's why the authors recommend pipx for installing nvitop. I am not a sysadmin, but I prefer pipx over relying on the (often outdated) distro sources.
https://github.com/XuehaiPan/nvitop?tab=readme-ov-file#insta...
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Why does stable diffusion hold onto my vram even when it’s doing nothing. It works great for a few images and then it racks up so much vram usage it just won’t do anything anymore and errors out. Is there a way to free up VRAM every so often? RX 6700XT 12GB VRAM
Hey, thanks for that. I think I found what you mentioned: https://github.com/XuehaiPan/nvitop
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How to make a deep learning engineer happy in one command? `nvidia-smi`:
nvitop
- Prédiction de séries chronologiques avec une carte GPU dans Paperspace Gradient et le langage Julia…
tmu
- Tsetlin machine – the other AI toolbooks
- Tsetlin Machine Unified (TMU) - One Codebase to Rule Them All
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[R] New Tsetlin machine learning scheme creates up to 80x smaller logical rules, benefitting hardware efficiency and interpretability.
Code: https://github.com/cair/tmu
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This Artificial Intelligence (AI) Research From Norway Introduces Tsetlin Machine-Based Autoencoder For Representing Words Using Logical Expressions
Quick Read: https://www.marktechpost.com/2023/01/10/this-artificial-intelligence-ai-research-from-norway-introduces-tsetlin-machine-based-autoencoder-for-representing-words-using-logical-expressions/ Paper: https://arxiv.org/pdf/2301.00709.pdf Github: https://github.com/cair/tmu
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Do we really need 300 floats to represent the meaning of a word? Representing words with words - a logical approach to word embedding using a self-supervised Tsetlin Machine Autoencoder.
Here is a new self-supervised machine learning approach that captures word meaning with concise logical expressions. The logical expressions consist of contextual words like “black,” “cup,” and “hot” to define other words like “coffee,” thus being human-understandable. I raise the question in the heading because our logical embedding performs competitively on several intrinsic and extrinsic benchmarks, matching pre-trained GLoVe embeddings on six downstream classification tasks. Thanks to my clever PhD student Bimal, we now have even more fun and exciting research ahead of us. Our long term research goal is, of course, to provide an energy efficient and transparent alternative to deep learning. You find the paper here: https://arxiv.org/abs/2301.00709 , an implementation of the Tsetlin Machine Autoencoder here: https://github.com/cair/tmu, and a simple word embedding demo here: https://github.com/cair/tmu/blob/main/examples/IMDbAutoEncoderDemo.py.
What are some alternatives?
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scikit-cuda - Python interface to GPU-powered libraries
stable-diffusion-webui-directml - Stable Diffusion web UI
PyCUDA - CUDA integration for Python, plus shiny features
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pyopencl - OpenCL integration for Python, plus shiny features
gpu-operator - NVIDIA GPU Operator creates/configures/manages GPUs atop Kubernetes
TsetlinMachine - Code and datasets for the Tsetlin Machine
pg_activity - pg_activity is a top like application for PostgreSQL server activity monitoring.
catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.