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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.
Let's finetune video generation models!
| Date | Stars |
|---|---|
| 2026-07-24 | 551 |
| 2026-07-25 | 551 |
| 2026-07-28 | 551 |
| 2026-07-30 | 551 |
| 2026-08-06 | 551 |
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<p align="center" width="50%"> <img src="https://github.com/user-attachments/assets/38efb5bc-723e-4012-aebd-f55723c593fb" alt="VideoTuna" style="width: 75%; min-width: 450px; display: block; margin: auto; background-color: transparent;"> </p> # VideoTuna   [](https://discord.gg/AammaaR2) <a href='https://github.com/user-attachments/assets/a48d57a3-4d89-482c-8181-e0bce4f750fd'><img src='https://badges.aleen42.com/src/wechat.svg'></a> [](https://videoverses.github.io/videotuna/) [](https://github.com/VideoVerses/VideoTuna) 🤗🤗🤗 Videotuna is a useful codebase for text-to-video applications. 🌟 VideoTuna is the first repo that integrates multiple AI video generation models including `text-to-video (T2V)`, `image-to-video (I2V)`, `text-to-image (T2I)`, and `video-to-video (V2V)` generation for model inference and finetuning (to the best of our knowledge). 🌟 VideoTuna is the first repo that provides comprehensive pipelines in video generation, from fine-tuning to pre-training, continuous training, and post-training (alignment) (to the best of our knowledge). ## 🔆 Features  🌟 **All-in-one framework:** Inference and fine-tune various up-to-date pre-trained video generation models. 🌟 **Continuous training:** Keep improving your model with new data. 🌟 **Fine-tuning:** Adapt pre-trained models to specific domains. 🌟 **Human preference alignment:** Leverage RLHF to align with human preferences. 🌟 **Post-processing:** Enhance and rectify the videos with video-to-video enhancement model. ## 🔆 Updates - [2025-04-22] 🐟 Supported **inference** for `Wan2.1` and `Step Video` and **fine-tuning** for `HunyuanVideo T2V`, with a unified codebase architecture. - [2025-02-03] 🐟 Supported automatic code formatting via [PR#27](https://github.com/VideoVerses/VideoTuna/pull/27). Thanks [@samidarko](https://github.com/samidarko)! - [2025-02-01] 🐟 Migrated to [Poetry](https://python-poetry.org) for streamlined dependency and script management ([PR#25](https://github.com/VideoVerses/VideoTuna/pull/25)). Thanks [@samidarko](https://github.com/samidarko)! - [2025-01-20] 🐟 Supported **fine-tuning** for `Flux-T2I`. - [2025-01-01] 🐟 Released **training** for `VideoVAE+` in the [VideoVAEPlus repo](https://github.com/VideoVerses/VideoVAEPlus). - [2025-01-01] 🐟 Supported **inference** for `Hunyuan Video` and `Mochi`. - [2024-12-24] 🐟 Released `VideoVAE+`: a SOTA Video VAE model—now available in [this repo](https://github.com/VideoVerses/VideoVAEPlus)! Achieves better video reconstruction than NVIDIA’s [`Cosmos-Tokenizer`](https://github.com/NVIDIA/Cosmos-Tokenizer). - [2024-12-01] 🐟 Supported **inference** for `CogVideoX-1.5-T2V&I2V` and `Video-to-Video Enhancement` from ModelScope. - [2024-12-01] 🐟 Supported **fine-tuning** for `CogVideoX`. - [2024-11-01] 🐟 🎉 Released **VideoTuna v0.1.0**! Initial support includes inference for `VideoCrafter1-T2V&I2V`, `VideoCrafter2-T2V`, `DynamiCrafter-I2V`, `OpenSora-T2V`, `CogVideoX-1-2B-T2V`, `CogVideoX-1-T2V`, `Flux-T2I`, and training/fine-tuning of `VideoCrafter`, `DynamiCrafter`, and `Open-Sora`. ## 🔆 Get started ### 1.Prepare environment #### (1) If you use Linux and Conda (Recommend) ``` shell conda create -n videotuna python=3.10 -y conda activate videotuna pip install poetry poetry install ``` - ↑ It takes around 3 minitues. **Optional: Flash-attn installation** Hunyuan model uses it to reduce memory usage and speed up inference. If it is not installed, the model will run in normal mode. Install the `flash-
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mayuema · HKUST · Hong Kong
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:73e9e5ea7982f784, topic:video-generation, topic:text-to-video, desc:video generation