Feature Examples
## Citations
Use `[@key]` to cite papers. Citations are auto-numbered and collected in a References section.
**Syntax:**
```markdown
The transformer architecture [@vaswani2017attention] revolutionized NLP.
Multiple citations: [@devlin2019bert; @brown2020gpt3]
```
**Result:**
The transformer architecture [@vaswani2017attention] revolutionized NLP.
---
## Cross-References
Label and reference figures, tables, and equations.
**Syntax:**
```markdown
{#fig:attn}
As shown in {@fig:attn}, the attention pattern...
| Col A | Col B |{#tbl:results}
See {@tbl:results} for results.
$$E = mc^2 \label{eq:einstein}$$
Equation \eqref{eq:einstein} shows...
```
---
## Inline Formatting
**Highlights:**
```markdown
This is ==highlighted text== in your content.
```
Result: This is ==highlighted text== for emphasis.
**Keyboard shortcuts:**
```markdown
Press [[Ctrl+C]] to copy.
```
Result: Press [[Ctrl+C]] to copy.
**Abbreviations:**
```markdown
The ::GPU|Graphics Processing Unit:: accelerates training.
```
Result: The ::GPU|Graphics Processing Unit:: accelerates training.
---
## Callout Blocks
> [!NOTE]
> Basic information or context.
> [!TIP]
> Helpful suggestions.
> [!WARNING]
> Important cautions.
> [!THEOREM]
> For any bounded sequence, there exists a convergent subsequence.
> [!DEFINITION]
> A **metric space** is a set equipped with a distance function.
> [!PROOF]
> By contradiction, assume the opposite and derive a contradiction. ∎
> [!EXAMPLE]
> Consider $f(x) = x^2$ on the interval $[0, 1]$.
**Syntax:**
```markdown
> [!TYPE]
> Content here...
```
Available types: `NOTE`, `TIP`, `WARNING`, `DANGER`, `QUESTION`, `THEOREM`, `DEFINITION`, `PROOF`, `EXAMPLE`, `CRITICAL`, `SUCCESS`, `ABSTRACT`
---
## Math (LaTeX)
**Inline:** `$E = mc^2$` → $E = mc^2$
**Display:**
```latex
$$
\int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi}
$$
```
$$
\int_{-\infty}^{\infty} e^{-x^2} dx = \sqrt{\pi}
$$
---
## Interactive Code
---
## Collapsible Code
---
## Embeds
**HuggingFace Space:**
```html
```
**Video (YouTube/Vimeo/local):**
```html
```
---
## Image Comparison
```html
```
---
## Notes
Notes are organized by subject at `/notes/`. They support all features above plus:
- Subject-based navigation
- Related notes suggestions
- Backlinks
Create notes in `_notes/` folder:
```yaml
---
title: "Note Title"
subject: "Transformers"
tags: [attention, nlp]
---
```
# This code runs in your browser!
import numpy as np
x = np.linspace(0, 2*np.pi, 100)
print(f"Sum of sin(x): {np.sum(np.sin(x)):.4f}")
print(f"Max of cos(x): {np.max(np.cos(x)):.4f}")
class AttentionHead:
def __init__(self, d_model, d_k):
self.W_q = np.random.randn(d_model, d_k)
self.W_k = np.random.randn(d_model, d_k)
self.W_v = np.random.randn(d_model, d_k)
def forward(self, x):
Q = x @ self.W_q
K = x @ self.W_k
V = x @ self.W_v
scores = Q @ K.T / np.sqrt(self.d_k)
return softmax(scores) @ V