Update README.md

README.md

@@ -1,13 +1,37 @@
 ---
-license: openrail
+license: creativeml-openrail-m
 ---
 
-This model intends to replicate the generic style of the interior of a TARDIS. The first dataset (82 pictures) focusses on the console a little too much, but training 2k steps only helped complete what was already in the original model this was based on, RunwayML 1.5
-All doctor who seasons were used, with no distinction in the prompt.
+# TARDISfusion
+<p>
+	<img src="https://huggingface.co/Guizmus/Tardisfusion/raw/main/showcase.jpg"/><br/>
+	This is a Dreamboothed Stable Diffusion model trained on 3 Style concepts.<br/>
+	The total dataset is made of 209 pictures, and the training has been done on runawayml 1.5 with 2500 steps and the new VAE.
+	The following tokens will add their corresponding concept :<br/>
+	<ul>
+		<li><b>Classic Tardis style</b> : Architectural and furniture style seen inside the TARDIS in the series before the reboot.</li>
+		<li><b>Modern Tardis style</b>: Architectural and furniture style seen inside the TARDIS in the series after the reboot</li>
+		<li><b>Tardis Box style</b>: A style made from the TARDIS seen from the outside. Summons a TARDIS anywhere.</li>
+	</ul>
+</p>
 
-* Recommended sampling method : DPM2 a Karras, Euler a
-* Activation token : TardisRoom style
-* Best used on img2img
-* [download link](https://huggingface.co/Guizmus/Tardisfusion/resolve/main/Tardisfusion-v1.ckpt)
+## 🧨 Diffusers
 
-This first version is still rough, better ones should come soon.
+This model can be used just like any other Stable Diffusion model. For more information,
+please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion).
+
+You can also export the model to [ONNX](https://huggingface.co/docs/diffusers/optimization/onnx), [MPS](https://huggingface.co/docs/diffusers/optimization/mps) and/or [FLAX/JAX]().
+
+```python
+from diffusers import StableDiffusionPipeline
+import torch
+
+model_id = "Guizmus/Tardisfusion"
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
+
+prompt = "a bedroom, Classic Tardis style"
+image = pipe(prompt).images[0]
+
+image.save("./TARDIS Style.png")
+```