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README.md

@@ -69,6 +69,11 @@ print(generated_text)
   - `"kl"`: KL divergence (D_KL(candidate || target)) - measures how much information is lost when using the candidate distribution to approximate the target
   - `"js"`: Jensen-Shannon divergence - a symmetric and bounded measure of distribution similarity
   - `"draft_tokens"`: Absolute difference between draft and target model probability of drafted token
+- **`track_acceptance_metrics`** (bool, default: False): Whether to track and return draft token acceptance statistics. When enabled, the output includes:
+  - `draft_token_acceptance_rate`: Ratio of accepted draft tokens to total draft tokens
+  - `total_draft_tokens`: Total number of draft tokens generated
+  - `total_accepted_tokens`: Total number of draft tokens accepted
+  Set to `True` when you need to analyze acceptance rates for performance evaluation. When `False` (default), no tracking computation is performed, minimizing overhead for production use.
 
 ### How It Works