address review comments

Signed-off-by: h-guo18 <[email protected]>

Author: h-guo18

examples/speculative_decoding/README.md

@@ -86,7 +86,7 @@ We can optionally use smaller vocab size for the draft model for faster training
 python calibrate_draft_vocab.py --model meta-llama/Llama-3.2-1B-Instruct --data Daring-Anteater/train.jsonl --draft_vocab_size 32000 --save_dir draft_vocab_cache
 ```
 
-This will produce a `d2t.pt` file in `save_dir`, which is the mapping from draft vocabs to full vocab that will be read by our draft model later.
+This will produce a `d2t.pt` file in `save_dir`, which is the mapping from draft token to target token. During inference, draft tokens can be mapped back to target tokens by `target_token = draft_token + d2t[draft_token]`.
 
 ### (Optional) Configuring Draft Model