keepsake
speech-enhancement
keepsake | speech-enhancement | |
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4 | 3 | |
1,637 | 22 | |
0.0% | - | |
0.0 | 0.0 | |
about 1 year ago | over 4 years ago | |
Python | Python | |
Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
keepsake
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keepsake VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
- [D] Experiment Tracking Today: What do you use? Pros and cons.
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[D] How to properly version control ML models amid rapid experimentation?
Keepsake
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[D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit?
Complementing the given answer, you could check https://github.com/replicate/keepsake for model versioning.
speech-enhancement
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[Discussion] The most painful thing about machine learning
I find writing smoke tests (described here, code examples: model tests + training loop tests) and running them on every commit in CI (eg GitHub Actions) catches a lot of problem. Using pydantic is good for keeping any config files valid is good - you can smoke test those as well.
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[D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit?
Even if detailed unit testing is hard, you can smoke test your models in CI to make sure that they're at least not crashing. More on smoke tests here. Some example smoke tests for a neural net here. Running your tests in GitHub Actions is relatively easy (here).
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[D] How did you manage GPU instances in the public cloud?
use Packer to pre-build an Amazon Machine Image (AMI) to pre-install all the garbage you need to run your code (eg NVIDIA stuff)
What are some alternatives?
dvc - 🦉 ML Experiments and Data Management with Git
summer - A compartmental disease modelling framework (Python)
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
nestedcvtraining
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Python Packages Project Generator - 🚀 Your next Python package needs a bleeding-edge project structure.
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
NumPy - The fundamental package for scientific computing with Python.
guildai - Experiment tracking, ML developer tools
Samosa (समोसा) - Enforce a triangular Git workflow. If this is not possible, explain why.
pydantic - Data validation using Python type hints