Add a usage example to the model card

README.md

@@ -12,6 +12,21 @@ language:
 pipeline_tag: automatic-speech-recognition
 ---
 
+## Usage
+
+```python
+import librosa
+from espnet2.bin.asr_inference import Speech2Text
+
+speech2text = Speech2Text.from_pretrained(model_tag="espnet/UniverSLU-17-Task-Specifier")
+# librosa resamples and mixes to one channel, so any file works; 16000 is
+# what nearly every espnet recogniser is trained on - check this model's
+# config if its audio is not 16 kHz
+speech, rate = librosa.load("audio.wav", sr=16000, mono=True)
+text, *_ = speech2text(speech)[0]
+print(text)
+```
+
 ## UniverSLU-17 Task Specifier
 
 UniverSLU-17 Task Specifier is a Multi-task Spoken Language Understanding model from CMU WAVLab.