Update README.md

README.md

@@ -25,7 +25,7 @@ model-index:
       type: librispeech_asr
       config: clean
       split: test
-      args: 
+      args:
         language: en
     metrics:
     - name: Test WER
@@ -39,12 +39,13 @@ model-index:
       type: librispeech_asr
       config: other
       split: test
-      args: 
+      args:
         language: en
     metrics:
     - name: Test WER
       type: wer
-      value: 9.0
+      value: 9
+library_name: diffusers
 ---
 
 # SWRA (SWARA)
@@ -129,4 +130,4 @@ print("WER:", wer.compute(predictions=result["transcription"], references=result
 ## Training data
 
 The S2T-SMALL-LIBRISPEECH-ASR is trained on [LibriSpeech ASR Corpus](https://www.openslr.org/12), a dataset consisting of
-approximately 1000 hours of 16kHz read English speech.
+approximately 1000 hours of 16kHz read English speech.