Create awsome Solveit slides
Project description
sslides
Usage
Installation
Install latest from the GitHub repository:
$ pip install git+https://github.com/rleyvasal/sslides.git
or from pypi
$ pip install sslides
Documentation
Documentation can be found hosted on this GitHub repository’s pages. Additionally you can find package manager specific guidelines on pypi.
How to use
- Import sslides functions
from sslides import sshow ssave - Create a note with
#| sto tell sslides all markdown below are your slides - The first note with # header becomes the title page
- Create as many slides as you want with ## header - all content below that heading is the slide content
- At the end of slides show or save (standalone html)
sshow()orssave()
from sslides import sshow
If you are new to using nbdev here are some useful pointers to get you
started.
Introducing sslides
What is sslides
A tool for creating beautiful presentations from your solveit dialogs
and research. - At the end of dialog create your slides - #| s marks
the begining of slides - All Markdown and code cells below will be in
slides - Code and code output hidden in dialog will be hidden in the
slides - Navigate with arrow keys or hover on bottom right to see
controls
Content Suported
- Markdown
- Bullet lists
- Latex Math
- Attachments from screenshots
- Code - highlighted by Pygments
Latex - Content too long, scroll option
Scaled Dot-Product Attention
The attention mechanism from “Attention is All You Need”:
$$\text{Attention}(Q, K, V) = \text{softmax}\left(\frac{QK^T}{\sqrt{d_k}}\right)V$$
Where $Q$ is queries, $K$ is keys, $V$ is values, and $d_k$ is the dimension of the keys.
Math Examples
Inline math: The quadratic formula is $x = \frac{-b \pm \sqrt{b^2-4ac}}{2a}$
Display math: $$\int_a^b f(x)dx = F(b) - F(a)$$
Statistics: $$\bar{x} = \frac{1}{n}\sum_{i=1}^n x_i$$
Calculus derivative: $$\frac{d}{dx}(x^n) = nx^{n-1}$$
Matrix: $$\begin{bmatrix} a & b \ c & d \end{bmatrix}$$
Attachments
Plots
Activation Functions Comparisons
- Code hidden in Solveit = Code hidden in slides
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(-3, 3, 1000)
# Activation functions
relu = np.maximum(0, x)
gelu = 0.5 * x * (1 + np.tanh(np.sqrt(2/np.pi) * (x + 0.044715 * x**3)))
swish = x / (1 + np.exp(-x))
leaky_relu = np.where(x > 0, x, 0.01 * x)
fig, ax = plt.subplots(figsize=(10, 6))
ax.plot(x, relu, label='ReLU', linewidth=2)
ax.plot(x, gelu, label='GELU', linewidth=2)
ax.plot(x, swish, label='Swish', linewidth=2)
ax.plot(x, leaky_relu, label='Leaky ReLU', linewidth=2, linestyle='--')
ax.axhline(0, color='black', linewidth=0.5, alpha=0.3)
ax.axvline(0, color='black', linewidth=0.5, alpha=0.3)
ax.grid(True, alpha=0.3)
ax.legend(fontsize=12)
ax.set_xlabel('Input', fontsize=12)
ax.set_ylabel('Output', fontsize=12)
ax.set_title('Activation Functions Comparison', fontsize=14, pad=15)
plt.tight_layout()
plt.show()
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