Update app.py

app.py

@@ -5,7 +5,7 @@ import pytube as pt
 from transformers import pipeline
 from huggingface_hub import model_info
 
-MODEL_NAME = "openai/whisper-medium"
+MODEL_NAME = "cloudqi/cqi_speech_recognize_pt_v0"
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -18,18 +18,18 @@ pipe = pipeline(
 
 langs = model_info(MODEL_NAME).cardData["language"]
 
-article = f"<details><summary>This model supports {len(langs)} languages! (Click to expand)</summary>> {langs}</details>"
+article = f"<details><summary>Esse modelo suporta as linguas {len(langs)} ! (Clique para expandir)</summary>> {langs}</details>"
 
 def transcribe(microphone, file_upload):
     warn_output = ""
     if (microphone is not None) and (file_upload is not None):
         warn_output = (
-            "WARNING: You've uploaded an audio file and used the microphone. "
+            "WARNING: Você carregou um arquivo de áudio e usou o microfone. "
             "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
         )
 
     elif (microphone is None) and (file_upload is None):
-        return "ERROR: You have to either use the microphone or upload an audio file"
+        return "ERROR: Transcreva microfones longos ou entradas de áudio com o clique de um botão"
 
     file = microphone if microphone is not None else file_upload
 
@@ -69,9 +69,9 @@ mf_transcribe = gr.Interface(
     outputs="text",
     layout="horizontal",
     theme="huggingface",
-    title="Whisper Demo: Transcribe Audio",
+    title="Demonstração: Transcrever Audio",
     description=(
-        "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the the fine-tuned"
+        "Transcreva microfones longos ou entradas de áudio com o clique de um botão! Demo uses the the fine-tuned"
         f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
         " of arbitrary length."
     ),
@@ -85,9 +85,9 @@ yt_transcribe = gr.Interface(
     outputs=["html", "text"],
     layout="horizontal",
     theme="huggingface",
-    title="Whisper Demo: Transcribe YouTube",
+    title="Demonstração: Transcrever do YouTube",
     description=(
-        "Transcribe long-form YouTube videos with the click of a button! Demo uses the the fine-tuned checkpoint:"
+        "Gere legendas com um clique ! Demo uses the the fine-tuned checkpoint:"
         f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files of"
         " arbitrary length."
     ),