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simplify docs part ii (#190)

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* simplify docs.

* clarify the cog checkpoints supported.

* make the note smaller.

* replace with sub

* Apply suggestions from code review

Co-authored-by: Aryan <aryan@huggingface.co>

---------

Co-authored-by: Aryan <aryan@huggingface.co>
This commit is contained in:
Sayak Paul
2025-01-07 12:47:01 +05:30
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README.md
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@@ -135,14 +135,16 @@ For inference, refer [here](./docs/training/ltx_video.md#inference). For docs re
<div align="center">
| Model Name | Tasks | Ckpts Tested | Min. GPU<br>VRAM | Comments |
|:------------:|:---------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------------------:|:--------------------------------------------------------------:|
| [LTX-Video](https://huggingface.co/docs/diffusers/main/api/pipelines/ltx_video) | <ul><li>T2V ✅</li><li> I2V ❌</li></ul> | [Lightricks/LTX-Video](https://huggingface.co/Lightricks/LTX-Video) | 11 GB | Fast to train |
| [HunyuanVideo](https://huggingface.co/docs/diffusers/main/api/pipelines/hunyuan_video) | <ul><li>T2V ✅</li><li> I2V ❌</li></ul> | [tencent/HunyuanVideo](https://huggingface.co/tencent/HunyuanVideo) | 42 GB | - |
| [CogVideoX](https://huggingface.co/docs/diffusers/main/api/pipelines/cogvideox) | <ul><li>T2V ✅</li><li> I2V ❌</li></ul> | <ul><li>[THUDM/CogVideoX1.5-5B](https://huggingface.co/THUDM/CogVideoX1.5-5B)</li><li>[THUDM/CogVideoX-5b](https://huggingface.co/THUDM/CogVideoX-5b)</li><li>[THUDM/CogVideoX-2b](https://huggingface.co/THUDM/CogVideoX-2b)</li> | - GB | Training with multi-bucket, multi-resolution frames is supported. |
| **Model Name** | **Tasks** | **Min. GPU VRAM** |
|:---:|:---:|:---:|
| [LTX-Video](./docs/training/ltx_video.md) | Text-to-Video | 11 GB |
| [HunyuanVideo](./docs/training/hunyuan_video.md) | Text-to-Video | 42 GB |
| [CogVideoX](./docs/training/cogvideox.md) | Text-to-Video | 12GB<sup>*</sup> |
</div>
<sub><sup>*</sup>Noted for the 5B variant.</sub>
Note that the memory consumption in the table is reported with most of the options, discussed in [docs/training/optimizations](./docs/training/optimization.md), enabled.
If you would like to use a custom dataset, refer to the dataset preparation guide [here](./docs/dataset/README.md).