Add 'Run with vLLM' section (OpenAI-compatible transcription API)

README.md

@@ -66,6 +66,58 @@ print(hyp)
 
 Audio > 35 s is automatically chunked. Input is resampled to 16 kHz internally.
 
+## Run with vLLM (OpenAI-compatible API)
+
+vLLM can serve the model behind an OpenAI-compatible `/v1/audio/transcriptions` endpoint — convenient for high-throughput batch transcription and remote serving.
+
+### Install
+
+```bash
+pip install "vllm==0.19.0"
+pip install "vllm[audio]" librosa   # audio deps are required for transcription
+```
+
+### Start the server
+
+```bash
+vllm serve syvai/hviske-v5.1 --trust-remote-code --host 0.0.0.0 --port 8000
+```
+
+`--trust-remote-code` is required — the model ships custom code. The runner (transcription) is auto-detected; no `--task` flag is needed.
+
+### Transcribe — curl
+
+```bash
+curl -s http://localhost:8000/v1/audio/transcriptions \
+  -F "file=@your_audio.wav" \
+  -F "model=syvai/hviske-v5.1" \
+  -F "language=da" \
+  -F "temperature=0"
+```
+
+### Transcribe — Python (`openai` client)
+
+```python
+from openai import OpenAI
+
+client = OpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY")
+
+with open("your_audio.wav", "rb") as f:
+    resp = client.audio.transcriptions.create(
+        model="syvai/hviske-v5.1",
+        file=f,
+        language="da",
+        temperature=0,
+    )
+print(resp.text)
+```
+
+**Notes**
+
+- `language="da"` + `temperature=0` gives the most accurate, deterministic output.
+- `response_format` supports `json` (default) and `text`. `verbose_json` is **not** supported and returns a 400.
+- Accepts common audio formats (wav, mp3, flac, ogg); audio is resampled to 16 kHz internally.
+
 ## Training details
 
 - **Architecture:** 2.06B-parameter Conformer encoder-decoder, full fine-tune