aim
nvidia-gpu-scheduler
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aim | nvidia-gpu-scheduler | |
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70 | 1 | |
4,711 | 7 | |
3.9% | - | |
7.9 | 0.0 | |
1 day ago | over 1 year ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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aim
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aim VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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Using MLflow(Machine Learning experimentation tracking tool) in Kaggle notebooks with the help of DagsHub
Here is the codebase of aimlflow https://github.com/aimhubio/aimlflow and Aim https://github.com/aimhubio/aim
You can also check out Aim, which has an integration with MLflow, called aimlflow.
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Effortless image tracking and analysis for 3D segmentation task with Aim
Aim: An easy-to-use & supercharged open-source AI metadata tracker aimstack.io
⭐️ If you find Aim useful, please stop by https://github.com/aimhubio/aim and drop us a star.
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🦜🔗 Building Multi task AI agent with LangChain and using Aim to trace and visualize the executions
aimstack.io
Here you can find more use-cases: https://github.com/aimhubio/aim/blob/feature/add-langchain-on-docs/docs/source/using/langchain.md
aimstack.io
Hi u/LetGoAndBeReal, Sorry for the inconvenience , here is the link to Aim docs https://github.com/aimhubio/aim/blob/feature/add-langchain-on-docs/docs/source/using/langchain.md feel free to use.
nvidia-gpu-scheduler
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[D] How to be more productive while doing Deep Learning experiments?
Sure. No, a simple bash script is not enough. In my case, we have several machines shared in the department, some with GPUs, some without. What I have is a python script that gets a list of jobs and then it schedule them in the first available machine (according to memory/CPU/GPU availability). Unfortunately, what I have is really entangled with our computing platform (Docker-based with a shared filesystem) and not really easy to have it as standalone project (that's why I said "know you infrastructure"). The most similar thing that I could find online is this project. I believe there are then some HPC tools that could be useful (e.g. Slurm), but that's way too much for what we need.
What are some alternatives?
tensorboard - TensorFlow's Visualization Toolkit
dvc - 🦉 ML Experiments and Data Management with Git
guildai - Experiment tracking, ML developer tools
wandb - 🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
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]
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
keepsake - Version control for machine learning
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
fastapi-cloud-tasks - GCP's Cloud Tasks + Cloud Scheduler + FastAPI = Partial replacement for celery.