Update docs/source/en/training/cogvideox.md

Co-authored-by: Steven Liu <[email protected]>

Author: glide-the

docs/source/en/training/cogvideox.md

@@ -200,7 +200,7 @@ To better track our training experiments, we're using the following flags in the
 * `--report_to wandb` will ensure the training runs are tracked on Weights and Biases. To use it, be sure to install `wandb` with `pip install wandb`.
 * `validation_prompt` and `validation_epochs` to allow the script to do a few validation inference runs. This allows us to qualitatively check if the training is progressing as expected.
 
-Note that setting the `<ID_TOKEN>` is not necessary. From some limited experimentation, we found it to work better (as it resembles [Dreambooth](https://huggingface.co/docs/diffusers/en/training/dreambooth) like training) than without. When provided, the ID_TOKEN is appended to the beginning of each prompt. So, if your ID_TOKEN was `"DISNEY"` and your prompt was `"Spiderman swinging over buildings"`, the effective prompt used in training would be `"DISNEY Spiderman swinging over buildings"`. When not provided, you would either be training without any such additional token or could augment your dataset to apply the token where you wish before starting the training.
+Setting the `<ID_TOKEN>` is not necessary. From some limited experimentation, we found it works better (as it resembles [Dreambooth](https://huggingface.co/docs/diffusers/en/training/dreambooth) training) than without. When provided, the `<ID_TOKEN>` is appended to the beginning of each prompt. So, if your `<ID_TOKEN>` was `"DISNEY"` and your prompt was `"Spiderman swinging over buildings"`, the effective prompt used in training would be `"DISNEY Spiderman swinging over buildings"`. When not provided, you would either be training without any additional token or could augment your dataset to apply the token where you wish before starting the training.
 
 > [!TIP]
 > You can pass `--use_8bit_adam` to reduce the memory requirements of training.