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Fix the broken image url and links (#1988)
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examples/generative/ipynb/random_walks_with_stable_diffusion_3.ipynb

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"a point on the manifold back to a displayable image is called \"decoding\" -- in\n",
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"the Stable Diffusion model, this is handled by the \"decoder\" model.\n",
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"\n",
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"![Stable Diffusion 3 Medium Architecture](https://huggingface.co/stabilityai/stable-diffusion-3-medium/resolve/main/mmdit.png)\n",
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"![Stable Diffusion 3 Medium Architecture](/img/examples/generative/random_walks_with_stable_diffusion_3/mmdit.png)\n",
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"\n",
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"This latent manifold of images is continuous and interpolative, meaning that:\n",
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"\n",
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"high-dimensional data points, such as latent vectors used in generative models.\n",
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"\n",
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"The source is from Andrej Karpathy's gist:\n",
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"https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355.\n",
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"[https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355](https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355).\n",
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"\n",
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"A more detailed explanation of this method can be found at:\n",
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"https://en.wikipedia.org/wiki/Slerp."
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"[https://en.wikipedia.org/wiki/Slerp](https://en.wikipedia.org/wiki/Slerp)."
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]
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},
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{

examples/generative/md/random_walks_with_stable_diffusion_3.md

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a point on the manifold back to a displayable image is called "decoding" -- in
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the Stable Diffusion model, this is handled by the "decoder" model.
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![Stable Diffusion 3 Medium Architecture](https://huggingface.co/stabilityai/stable-diffusion-3-medium/resolve/main/mmdit.png)
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![Stable Diffusion 3 Medium Architecture](/img/examples/generative/random_walks_with_stable_diffusion_3/mmdit.png)
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This latent manifold of images is continuous and interpolative, meaning that:
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high-dimensional data points, such as latent vectors used in generative models.
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The source is from Andrej Karpathy's gist:
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https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355.
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[https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355](https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355).
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A more detailed explanation of this method can be found at:
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https://en.wikipedia.org/wiki/Slerp.
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[https://en.wikipedia.org/wiki/Slerp](https://en.wikipedia.org/wiki/Slerp).
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```python

examples/generative/random_walks_with_stable_diffusion_3.py

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a point on the manifold back to a displayable image is called "decoding" -- in
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the Stable Diffusion model, this is handled by the "decoder" model.
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![Stable Diffusion 3 Medium Architecture](https://huggingface.co/stabilityai/stable-diffusion-3-medium/resolve/main/mmdit.png)
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![Stable Diffusion 3 Medium Architecture](/img/examples/generative/random_walks_with_stable_diffusion_3/mmdit.png)
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This latent manifold of images is continuous and interpolative, meaning that:
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high-dimensional data points, such as latent vectors used in generative models.
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The source is from Andrej Karpathy's gist:
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https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355.
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[https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355](https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355).
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A more detailed explanation of this method can be found at:
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https://en.wikipedia.org/wiki/Slerp.
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[https://en.wikipedia.org/wiki/Slerp](https://en.wikipedia.org/wiki/Slerp).
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"""
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