Update README.md

README.md

@@ -7,29 +7,83 @@ tags:
 - text-to-image
 - diffusion-models-class
 - dreambooth-hackathon
-- animal
+- wildcard
 widget:
 - text: a photo of a ðŁĴŁ jellyfish in the snow
+- text: a photo of a ðŁĴŁ jellyfish next to a dog
+- text: a photo of a ðŁĴŁ jellyfish on top of a mountain
 ---
 
-# DreamBooth model for the ðŁĴŁ concept trained by simonschoe on a dataset of basic pokeballs (the plain white-red ones).
+# Iridescent Jellyfish
 
-This is a Stable Diffusion model fine-tuned on the ðŁĴŁ concept with DreamBooth. It can be used by modifying the `instance_prompt`: **a photo of ðŁĴŁ jellyfish**
+**Iridescent Jellyfish** is a Dreambooth model for the `iridescent` jellyfish concept (represented by the `ðŁĴŁ` identifier).
+It applies to the *animal* theme.
+It is fine-tuned from `runwayml/stable-diffusion-v1-5` checkpoint on a small dataset of jellyfish images.
+It can be used by modifying the `instance_prompt`: **a photo of a ðŁĴŁ jellyfish in the snow**
 
 This model was created as part of the DreamBooth Hackathon 🔥. Visit the [organisation page](https://huggingface.co/dreambooth-hackathon) for instructions on how to take part!
 
-## Description
+#### Fine-Tuning Details
 
+- Number of training images: 17
+- Learning rate: 2e-06
+- Training steps: 800
+- Guidance Scale: 7
+- Inference Steps: 50
 
-This is a Stable Diffusion model fine-tuned on `jellyfish` images for the animal theme.
+#### Output Examples
+
+<table>
+  <tr>
+    <td>a colorful sketch of a <b>ðŁĴŁ</b> jellyfish</td>
+    <td>a photo of a <b>ðŁĴŁ</b> jellyfish in the jungle</td>
+    <td>a mystic <b>ðŁĴŁ</b> jellyfish, trending on artstation</td>
+  </tr>
+  <tr>
+    <td align="center"><img src="https://huggingface.co/simonschoe/iridescent-jellyfish/resolve/main/output/jelly%20(1).png" style="height:200px"> </td>
+    <td align="center"><img src="https://huggingface.co/simonschoe/iridescent-jellyfish/resolve/main/output/jelly%20(2).png" style="height:200px"> </td>
+    <td align="center"><img src="https://huggingface.co/simonschoe/iridescent-jellyfish/resolve/main/output/jelly%20(3).png" style="height:200px"> </td>
+  </tr>
+  <tr>
+    <td>a oil painting of a <b>ðŁĴŁ</b> jellyfish</td>
+    <td>a photo of a <b>ðŁĴŁ</b> jellyfish next to a dog</td>
+    <td>a photo of a <b>ðŁĴŁ</b> jellyfish in the snow</td>
+  </tr>
+  <tr>
+    <td align="center"><img src="https://huggingface.co/simonschoe/iridescent-jellyfish/resolve/main/output/jelly%20(4).png" style="height:200px"> </td>
+    <td align="center"><img src="https://huggingface.co/simonschoe/iridescent-jellyfish/resolve/main/output/jelly%20(5).png" style="height:200px"> </td>
+    <td align="center"><img src="https://huggingface.co/simonschoe/iridescent-jellyfish/resolve/main/output/jelly%20(6).png" style="height:200px"> </td>
+  </tr>
+  <tr>
+    <td>a photo of a <b>ðŁĴŁ</b> jellyfish on top of a mountain</td>
+    <td>a photo of a <b>ðŁĴŁ</b> jellyfish in the sky</td>
+    <td>a photo of a <b>ðŁĴŁ</b> jellyfish</td>
+  </tr>
+  <tr>
+    <td align="center"><img src="https://huggingface.co/simonschoe/iridescent-jellyfish/resolve/main/output/jelly%20(7).png" style="height:200px"> </td>
+    <td align="center"><img src="https://huggingface.co/simonschoe/iridescent-jellyfish/resolve/main/output/jelly%20(8).png" style="height:200px"> </td>
+    <td align="center"><img src="https://huggingface.co/simonschoe/iridescent-jellyfish/resolve/main/output/jelly%20(9).png" style="height:200px"> </td>
+  </tr>
+</table>
 
 
 ## Usage
 
 ```python
 from diffusers import StableDiffusionPipeline
+import torch
+
+device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
+pipeline = StableDiffusionPipeline.from_pretrained('simonschoe/iridescent-jellyfish').to(device)
+
+prompt = "a photo of a ðŁĴŁ jellyfish in the snow"
+
+image = pipeline(
+    prompt,
+    num_inference_steps=50,
+    guidance_scale=7,
+    num_images_per_prompt=1
+).images[0]
 
-pipeline = StableDiffusionPipeline.from_pretrained('simonschoe/iridescent-jellyfish')
-image = pipeline().images[0]
 image
 ```