Fixes

app.py

@@ -1,6 +1,8 @@
 import sys
 import time
 
+from importlib.metadata import version
+
 import torch
 import torchaudio
 import torchaudio.transforms as T
@@ -8,7 +10,6 @@ import torchaudio.transforms as T
 import gradio as gr
 
 from transformers import AutoModelForCTC, Wav2Vec2BertProcessor
-from transformers import __version__ as transformers_version
 
 # Config
 model_name = "Yehor/w2v-bert-2.0-uk-v2"
@@ -109,10 +110,10 @@ tech_env = f"""
 tech_libraries = f"""
 #### Libraries
 
-- torch: {torch.__version__}
-- torchaudio: {torchaudio.__version__}
-- transformers: {transformers_version}
-- gradio: {gr.__version__}
+- torch: {version('torch')}
+- torchaudio: {version('torchaudio')}
+- transformers: {version('transformers')}
+- gradio: {version('gradio')}
 """.strip()
 
 
@@ -123,7 +124,7 @@ def inference(audio_path, progress=gr.Progress()):
     gr.Info("Starting recognition", duration=2)
 
     progress(0, desc="Recognizing")
-    
+
     meta = torchaudio.info(audio_path)
     duration = meta.num_frames / meta.sample_rate
 
@@ -147,7 +148,7 @@ def inference(audio_path, progress=gr.Progress()):
         audio_duration = meta.num_frames / meta.sample_rate
 
         audio_input, sr = torchaudio.load(path)
-        
+
         if meta.num_channels > 1:
             audio_input = torch.mean(audio_input, dim=0, keepdim=True)
 
@@ -234,9 +235,8 @@ with demo:
     gr.Markdown(description_foot)
 
     gr.Markdown("### Gradio app uses the following technologies:")
-    with gr.Row():
-        gr.Markdown(tech_env)
-        gr.Markdown(tech_libraries)
+    gr.Markdown(tech_env)
+    gr.Markdown(tech_libraries)
 
 if __name__ == "__main__":
     demo.queue()