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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
committed by GitHub
parent 38413aa167
commit 7b569daf55
4 changed files with 21 additions and 8 deletions
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docs/training/cogvideox.md
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@@ -109,6 +109,14 @@ Training configuration: {
| after validation end | 11.145 | 28.324 |
| after training end | 11.144 | 11.592 |
## Supported checkpoints
CogVideoX has multiple checkpoints as one can note [here](https://huggingface.co/collections/THUDM/cogvideo-66c08e62f1685a3ade464cce). The following checkpoints were tested with `finetrainers` and are known to be working:
* [THUDM/CogVideoX-2b](https://huggingface.co/THUDM/CogVideoX-2b)
* [THUDM/CogVideoX-5B](https://huggingface.co/THUDM/CogVideoX-5B)
* [THUDM/CogVideoX1.5-5B](https://huggingface.co/THUDM/CogVideoX1.5-5B)
## Inference
Assuming your LoRA is saved and pushed to the HF Hub, and named `my-awesome-name/my-awesome-lora`, we can now use the finetuned model for inference:
@@ -128,7 +136,8 @@ video = pipe("<my-awesome-prompt>").frames[0]
export_to_video(video, "output.mp4")
```
You can refer to the following guides to know more about performing LoRA inference in `diffusers`:
You can refer to the following guides to know more about the model pipeline and performing LoRA inference in `diffusers`:
* [CogVideoX in Diffusers](https://huggingface.co/docs/diffusers/main/en/api/pipelines/cogvideox)
* [Load LoRAs for inference](https://huggingface.co/docs/diffusers/main/en/tutorials/using_peft_for_inference)
* [Merge LoRAs](https://huggingface.co/docs/diffusers/main/en/using-diffusers/merge_loras)
docs/training/hunyuan_video.md
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@@ -171,7 +171,8 @@ output = pipe(
export_to_video(output, "output.mp4", fps=15)
```
You can refer to the following guides to know more about performing LoRA inference in `diffusers`:
You can refer to the following guides to know more about the model pipeline and performing LoRA inference in `diffusers`:
* [Hunyuan-Video in Diffusers](https://huggingface.co/docs/diffusers/main/api/pipelines/hunyuan_video)
* [Load LoRAs for inference](https://huggingface.co/docs/diffusers/main/en/tutorials/using_peft_for_inference)
* [Merge LoRAs](https://huggingface.co/docs/diffusers/main/en/using-diffusers/merge_loras)
docs/training/ltx_video.md
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@@ -159,7 +159,8 @@ video = pipe("<my-awesome-prompt>").frames[0]
export_to_video(video, "output.mp4", fps=8)
```
You can refer to the following guides to know more about performing LoRA inference in `diffusers`:
You can refer to the following guides to know more about the model pipeline and performing LoRA inference in `diffusers`:
* [LTX-Video in Diffusers](https://huggingface.co/docs/diffusers/main/en/api/pipelines/ltx_video)
* [Load LoRAs for inference](https://huggingface.co/docs/diffusers/main/en/tutorials/using_peft_for_inference)
* [Merge LoRAs](https://huggingface.co/docs/diffusers/main/en/using-diffusers/merge_loras)