Update app.py

app.py

@@ -2,6 +2,18 @@ import numpy as np
 import matplotlib.pyplot as plt
 import gradio as gr
 
+description = """## Token Probability Distribution Explorer
+
+This interactive tool lets you visualize how different parameters affect the probability distribution of tokens.
+
+- **Temperature**: Controls the randomness of predictions. Higher values (e.g., 2.0) make the distribution more uniform, while lower values (e.g., 0.1) make it peakier.
+- **Top-k**: Limits the number of most likely tokens to consider. For example, `top_k=5` means only the top 5 tokens are considered, and others are set to zero probability.
+- **Top-p (nucleus sampling)**: Limits the tokens to those whose cumulative probability mass is below a certain threshold. For instance, `top_p=0.9` means only tokens contributing to the top 90% of probability are considered.
+
+Adjust the sliders to see how each parameter influences the token probabilities. All tokens will always have some non-zero probability in the initial distribution.
+To learn more about LLM generation, check out the early release of [Hands-On Generative AI with Transformers and Diffusion Models](https://learning.oreilly.com/library/view/hands-on-generative-ai/9781098149239/).
+"""
+
 def get_initial_distribution(seed=42):
     np.random.seed(seed)  # For reproducibility
     token_probs = np.random.rand(10)
@@ -62,7 +74,9 @@ interface = gr.Interface(
         gr.Slider(0.0, 1.0, step=0.01, value=0.9, label="Top-p"),
     ],
     outputs=gr.Plot(label="Token Probability Distribution"),
-    live=True
+    live=True,
+    title="Explore generation parameters of LLMs",
+    description
 )
 
 interface.launch()