Update README (em-dash cleanup, doc edits)

README.md

@@ -43,7 +43,7 @@ Offline Russian speech-to-text with greedy RNN-T decoding. Same 16-layer Conform
 | Q5_K_M | [gigaam-v3-rnnt-Q5_K_M.gguf](https://huggingface.co/handy-computer/gigaam-v3-rnnt-gguf/resolve/main/gigaam-v3-rnnt-Q5_K_M.gguf) | 196 MB | 8.12% |
 | Q4_K_M | [gigaam-v3-rnnt-Q4_K_M.gguf](https://huggingface.co/handy-computer/gigaam-v3-rnnt-gguf/resolve/main/gigaam-v3-rnnt-Q4_K_M.gguf) | 175 MB | 8.12% |
 
-WER measured on the full FLEURS ru test split (775 utterances) with greedy decoding and no external LM. F32 reference baseline: 8.08%. Upstream `gigaam` author package measured on the same manifest: 9.46% — the 1.4 pp gap is upstream rejecting 5 long (>25 s) utterances with `Too long wav file, use 'transcribe_longform' method.` (counted as 100% deletion errors). On the 770-utt subset both sides decode, transcribe.cpp matches upstream exactly. ai-sage does not publish a FLEURS ru WER; this number is measured here.
+WER measured on the full FLEURS ru test split (775 utterances) with greedy decoding and no external LM. F32 reference baseline: 8.08%. Upstream `gigaam` author package measured on the same manifest: 9.46%; the 1.4 pp gap is upstream rejecting 5 long (>25 s) utterances with `Too long wav file, use 'transcribe_longform' method.` (counted as 100% deletion errors). On the 770-utt subset both sides decode, transcribe.cpp matches upstream exactly. ai-sage does not publish a FLEURS ru WER; this number is measured here.
 
 
 ## Usage