Sampling Hyperparameters
Temperature (T)
1.0
Controls randomness: Lower = Deterministic peak; Higher = Flat uniform distribution.
Top-K Truncation
5
Limits sampling to the highest K candidate logits.
Top-P Nucleus Mass
0.99
Dynamically truncates tokens after cumulative probability exceeds Top-P.
Raw Logits Scrubber
| Token | Logit ($z_i$) | Exp $e^{z_i/T}$ | Prob $P(t_i)$ | Status |
|---|
Softmax Scaling Equation:
$$P(t_i) = \frac{\exp(z_i / T)}{\sum_j \exp(z_j / T)}$$
Active Mass: 100% |
Tokens Retained: 5
Context & Generated Sequence
0 tokens generated
The capital of France is
Visual Monte Carlo Token Sampler Tree
p5.js Particle Tree
Normalized Token Probabilities
Cumulative Probability Curve (Nucleus)
Sampling Step Telemetry Summary
cumulative_p_retained_count: 3
sampled_token: Paris
top_prob: 0.98003
| Step | Sampled Token | Probability | Logit | Temp | Top-K | Top-P |
|---|