diff --git a/examples/dreambooth/train_dreambooth_lora_sd3.py b/examples/dreambooth/train_dreambooth_lora_sd3.py
index 2c66c341f78f..fe2720047198 100644
--- a/examples/dreambooth/train_dreambooth_lora_sd3.py
+++ b/examples/dreambooth/train_dreambooth_lora_sd3.py
@@ -101,19 +101,37 @@ def save_model_card(
 
 ## Model description
 
-These are {repo_id} DreamBooth weights for {base_model}.
+These are {repo_id} DreamBooth LoRA weights for {base_model}.
 
-The weights were trained  using [DreamBooth](https://dreambooth.github.io/).
+The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [SD3 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sd3.md).
 
-LoRA for the text encoder was enabled: {train_text_encoder}.
+Was LoRA for the text encoder enabled? {train_text_encoder}.
 
 ## Trigger words
 
-You should use {instance_prompt} to trigger the image generation.
+You should use `{instance_prompt}` to trigger the image generation.
 
 ## Download model
 
-[Download]({repo_id}/tree/main) them in the Files & versions tab.
+[Download the *.safetensors LoRA]({repo_id}/tree/main) in the Files & versions tab.
+
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
+
+```py
+from diffusers import AutoPipelineForText2Image
+import torch
+pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-3-medium-diffusers', torch_dtype=torch.float16).to('cuda')
+pipeline.load_lora_weights('{repo_id}', weight_name='pytorch_lora_weights.safetensors')
+image = pipeline('{validation_prompt if validation_prompt else instance_prompt}').images[0]
+```
+
+### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
+
+- **LoRA**: download **[`diffusers_lora_weights.safetensors` here 💾](/{repo_id}/blob/main/diffusers_lora_weights.safetensors)**.
+    - Rename it and place it on your `models/Lora` folder.
+    - On AUTOMATIC1111, load the LoRA by adding `<lora:your_new_name:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
+
+For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
 
 ## License
 
diff --git a/examples/dreambooth/train_dreambooth_sd3.py b/examples/dreambooth/train_dreambooth_sd3.py
index c8f2fb1ac61b..9a72294c20bd 100644
--- a/examples/dreambooth/train_dreambooth_sd3.py
+++ b/examples/dreambooth/train_dreambooth_sd3.py
@@ -95,17 +95,22 @@ def save_model_card(
 
 These are {repo_id} DreamBooth weights for {base_model}.
 
-The weights were trained  using [DreamBooth](https://dreambooth.github.io/).
+The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [SD3 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sd3.md).
 
-Text encoder was fine-tuned: {train_text_encoder}.
+Was the text encoder fine-tuned? {train_text_encoder}.
 
 ## Trigger words
 
-You should use {instance_prompt} to trigger the image generation.
+You should use `{instance_prompt}` to trigger the image generation.
 
-## Download model
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
 
-[Download]({repo_id}/tree/main) them in the Files & versions tab.
+```py
+from diffusers import AutoPipelineForText2Image
+import torch
+pipeline = AutoPipelineForText2Image.from_pretrained('{repo_id}', torch_dtype=torch.float16).to('cuda')
+image = pipeline('{validation_prompt if validation_prompt else instance_prompt}').images[0]
+```
 
 ## License