Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
This series will take you on a journey from the fundamentals of NLP and Computer Vision to the cutting edge of Vision-Language Models.
| Date | Stars |
|---|---|
| 2026-07-31 | 1179 |
| 2026-08-10 | 1178 |
| 2026-08-24 | 1179 |
| 2026-09-09 | 1180 |
| 2026-09-10 | 1181 |
| 2026-09-14 | 1180 |
| 2026-09-15 | 1180 |
| 2026-09-25 | 1181 |
| 2026-10-01 | 1182 |
| 2026-10-07 | 1181 |
| 2026-10-08 | 1182 |
| 2026-10-13 | 1182 |
| 2026-10-15 | 1183 |
| 2026-10-24 | 1184 |
| 2026-10-30 | 1185 |
| 2026-11-02 | 1186 |
| 2026-11-04 | 1186 |
Today
— stars today
This week
+2 stars this week
This month
+4 stars this month
Momentum
0.0
growth rate 0.17%/day
<div align="center"> <h1 align="center">VLMs zero-to-hero</h1> <p>coming: january 2025...</p> </div> # hello Welcome to VLMs Zero to Hero! This series will take you on a journey from the fundamentals of NLP and Computer Vision to the cutting edge of Vision-Language Models. # tutorials | **notebook** | **open in colab** | **video** | **paper** | |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------:|:---------------------------------------:| | 01.01. [Word2Veq: Distributed Representations of Words and Phrases and their Compositionality](https://github.com/SkalskiP/vlms-zero-to-hero/blob/master/01_natural_language_processing_fundamentals/01_01_word2vec_with_sub_sampling_and_negative_sampling_in_pytorch.ipynb) | [link](https://colab.research.google.com/github/SkalskiP/vlms-zero-to-hero/blob/master/01_natural_language_processing_fundamentals/01_01_word2vec_with_sub_sampling_and_negative_sampling_in_pytorch.ipynb) | soon | [link](https://arxiv.org/abs/1310.4546) | # roadmap ## natural language processing (NLP) fundamentals - Word2Veq: [Efficient Estimation of Word Representations in Vector Space](https://arxiv.org/pdf/1301.3781) (2013) and [Distributed Representations of Words and Phrases and their Compositionality](https://arxiv.org/pdf/1310.4546) (2013) - Seq2Seq: [Sequence to Sequence Learning with Neural Networks](https://arxiv.org/pdf/1409.3215) (2014) - [Attention Is All You Need](https://arxiv.org/pdf/1706.03762) (2017) - BERT: [Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/pdf/1810.04805) (2018) - GPT: [Improving Language Understanding by Generative Pre-Training](https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf) (2018) ## computer vision (CV) fundamentals - AlexNet: [ImageNet Classification with Deep Convolutional Neural Networks](https://proceedings.neurips.cc/paper_files/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf) (2012) - VGG: [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://arxiv.org/pdf/1409.1556) (2014) - ResNet: [Deep Residual Learning for Image Recognition](https://arxiv.org/pdf/1512.03385) (2015) ## early vision-language models - [Show and Tell: A Neural Image Caption Generator](https://arxiv.org/pdf/1411.4555) (2014) and [Show, Attend and Tell: Neural Image Caption Generation with Visual Attention](https://arxiv.org/pdf/1502.03044) (2015) - [A Picture is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/pdf/2010.11929) (2020) - CLIP: [Learning Transferable Visual Models from Natural Language Supervision](https://arxiv.org/pdf/2103.00020) (2021) ## scale and efficiency - [Scaling Laws for Neural Language Models](https://arxiv.org/pdf/2001.08361) (2020) - LoRA: [Low-Rank Adaptation of Large Language Models](https://arxiv.org/pdf/2106.09685) (2021) - QLoRA: [Efficient Fine-tuning of Quantized LLMs](https://arxiv.org/pdf/2305.14314) (2023) ## modern vision-language models - Flamingo: [A Visual Language Model for Few-Shot Learning](h
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Piotr Skalski · @roboflow
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:1c9be772c7916d7a, topic:vision-language-model, topic:clip, desc:vision-language
matched fp:1c9be772c7916d7a, topic:lora, readme:fine-tuning, readme:fine tuning
matched fp:1c9be772c7916d7a, topic:computer-vision, desc:computer vision, readme:computer vision
matched fp:1c9be772c7916d7a, topic:natural-language-processing, readme:natural language processing