Update README.md

README.md

@@ -87,21 +87,21 @@ The model can be used with the [`pipeline`](https://huggingface.co/docs/transfor
 class to transcribe audio files of arbitrary length.
 
 ```python
-    from transformers import pipeline
+from transformers import pipeline
 
-    model_id = "BUT-FIT/EBranchRegulaFormer-medium"
-    pipe = pipeline("automatic-speech-recognition", model=model_id, feature_extractor=model_id, trust_remote_code=True)
-    # In newer versions of transformers (>4.31.0), there is a bug in the pipeline inference type.
-    # The warning can be ignored.
-    pipe.type = "seq2seq"
+model_id = "BUT-FIT/EBranchRegulaFormer-medium"
+pipe = pipeline("automatic-speech-recognition", model=model_id, feature_extractor=model_id, trust_remote_code=True)
+# In newer versions of transformers (>4.31.0), there is a bug in the pipeline inference type.
+# The warning can be ignored.
+pipe.type = "seq2seq"
 
-    # Standard greedy decoding
-    result = pipe("audio.wav")
+# Standard greedy decoding
+result = pipe("audio.wav")
 
-    # Beam search decoding with joint CTC-attention scorer
-    generation_config = pipe.model.generation_config
-    generation_config.ctc_weight = 0.5
-    generation_config.num_beams = 5
-    generation_config.ctc_margin = 0
-    result = pipe("audio.wav")
+# Beam search decoding with joint CTC-attention scorer
+generation_config = pipe.model.generation_config
+generation_config.ctc_weight = 0.3
+generation_config.num_beams = 5
+generation_config.ctc_margin = 0
+result = pipe("audio.wav")
 ```