carefree-learn
ludwig
| carefree-learn | ludwig | |
|---|---|---|
| 1 | 3 | |
| 400 | 10,877 | |
| - | 1.5% | |
| 9.8 | 9.5 | |
| 2 months ago | 2 days ago | |
| Python | Python | |
| MIT License | 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.
carefree-learn
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Show HN: AI magics meet Infinite draw board
Hi, thank you so much for the valuable advice and information!
If I didn't get you wrong, maybe another project (carefree-learn) meets your needs better: https://github.com/carefree0910/carefree-learn.
This is an old project, with a VERY outdated document, but all the features of carefree-creator can be achieved with one or few lines of code from carefree-learn.
Take the typical text to image feature as an example, here's a piece of minimal-working-codes:
```python
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?
carefree-creator - AI magics meet Infinite draw board.
nlp-recipes - Natural Language Processing Best Practices & Examples
ds2 - Easiest way to use AI models without coding (Web UI & API support)
data-structures-and-algorithms - Resources that I used to crack some big tech & startups interviews
autogluon - AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data [Moved to: https://github.com/autogluon/autogluon]
aimet - AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
autogluon - Fast and Accurate ML in 3 Lines of Code
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
ai-deadlines - :alarm_clock: AI conference deadline countdowns