Sample Project (All Elements)
Reference page showing every type of content block usable in a project file.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
Text and inline formatting
bold, italic, bold italic, strikethrough, inline code, external link.
Blockquote.
Ordered list:
- First
- Second
- Third
Unordered list:
- One
- Two
- Nested
Footnote reference1.
Single image
Image row
Zoomable image
Image + text column
Text sits next to the image. Markdown bold, italic, and inline code all work inside a column. Swap the order of the two <div class="col-md-*"> blocks to flip image and text. Change the split (4/8, 6/6, 3/9) to change relative widths.
Use align-items-center on the row to vertically center the image with the text, or align-items-start to top-align them.
PDF embed
PDF carousel
YouTube embed
Jupyter notebook
Google Colab link
Code blocks
Python:
import numpy as np
def softmax(x):
e_x = np.exp(x - np.max(x))
return e_x / e_x.sum()
print(softmax(np.array([1.0, 2.0, 3.0])))
Bash:
git clone https://github.com/user/repo.git
cd repo && pip install -r requirements.txt
JavaScript:
const greet = (name) => `Hello, ${name}!`;
console.log(greet("world"));
Math
Inline: \(E = mc^2\)
Display:
\[\frac{\partial \mathcal{L}}{\partial \theta} = \mathbb{E}_{x \sim p_\theta}\!\left[\nabla_\theta \log p_\theta(x)\, r(x)\right]\]Buttons
Project website GitHub repo Download PDF
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Footnote body. ↩