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Update README (em-dash cleanup, doc edits)

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@@ -43,7 +43,7 @@ Offline Russian speech-to-text with greedy RNN-T decoding. 16-layer Conformer en
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  | Q5_K_M | [gigaam-v3-e2e-rnnt-Q5_K_M.gguf](https://huggingface.co/handy-computer/gigaam-v3-e2e-rnnt-gguf/resolve/main/gigaam-v3-e2e-rnnt-Q5_K_M.gguf) | 197 MB | 5.42% |
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  | Q4_K_M | [gigaam-v3-e2e-rnnt-Q4_K_M.gguf](https://huggingface.co/handy-computer/gigaam-v3-e2e-rnnt-gguf/resolve/main/gigaam-v3-e2e-rnnt-Q4_K_M.gguf) | 175 MB | 5.36% |
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- WER measured on the full FLEURS ru test split (775 utterances) with greedy decoding and no external LM. F32 reference baseline: 5.35%. Upstream `gigaam` author package measured on the same manifest: 6.78% 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.
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  ## Usage
 
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  | Q5_K_M | [gigaam-v3-e2e-rnnt-Q5_K_M.gguf](https://huggingface.co/handy-computer/gigaam-v3-e2e-rnnt-gguf/resolve/main/gigaam-v3-e2e-rnnt-Q5_K_M.gguf) | 197 MB | 5.42% |
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  | Q4_K_M | [gigaam-v3-e2e-rnnt-Q4_K_M.gguf](https://huggingface.co/handy-computer/gigaam-v3-e2e-rnnt-gguf/resolve/main/gigaam-v3-e2e-rnnt-Q4_K_M.gguf) | 175 MB | 5.36% |
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+ WER measured on the full FLEURS ru test split (775 utterances) with greedy decoding and no external LM. F32 reference baseline: 5.35%. Upstream `gigaam` author package measured on the same manifest: 6.78%; 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.
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  ## Usage