Create README.md

README.md

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+---
+language:
+- en
+license: openrail++
+thumbnail: "https://huggingface.co/nitrosocke/Ghibli-Diffusion/resolve/main/images/ghibli-diffusion-thumbnail.jpg"
+tags:
+- stable-diffusion
+- text-to-image
+- image-to-image
+- diffusers
+
+---
+### Mad Max: Fury Road Diffusion (SD 2.0, 768x768)
+
+This is the fine-tuned Stable Diffusion model trained on images from Mad Max: Fury Road.
+Use the tokens **_mad_max_fr_** in your prompts for the effect.
+
+
+**Images rendered with the model:**
+Turn your favorite cars, city's, characters in fury road style.
+
+![Samples](https://huggingface.co/valhalla/mad_max_diffusion-sd2/resolve/main/mad-max-fr.png)
+
+
+### 🧨 Diffusers
+
+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, DPMSolverMultistepScheduler
+import torch
+model_id = "valhalla/mad_max_diffusion-sd2"
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to("cuda")
+pipe.enable_attention_slicing()
+pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+
+prompt = "The streets of Paris with eiffel tower in the background in the style of mad_max_fr"
+image = pipe(prompt, num_inference_steps=30).images[0]
+image.save("./paris-mad-max-fr.png")
+```