Update app.py

app.py

@@ -1,4 +1,27 @@
 # Use a pipeline as a high-level helper
 from transformers import pipeline
+import gradio as gr
+import os
 
-pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-german")
+# Load model directly
+#from transformers import AutoProcessor, AutoModelForCTC
+#processor = AutoProcessor.from_pretrained("jonatasgrosman/wav2vec2-large-xlsr-53-german")
+#model = AutoModelForCTC.from_pretrained("jonatasgrosman/wav2vec2-large-xlsr-53-german")
+
+
+pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-german")
+
+# save your HF API token from https:/hf.co/settings/tokens as an env variable to avoid rate limiting
+auth_token = os.getenv("auth_token")
+
+# automatically load the interface from a HF model 
+# you can remove the api_key parameter if you don't care about rate limiting. 
+demo = gr.load(
+    "huggingface/facebook/wav2vec2-base-960h",
+    title="Speech-to-text",
+    inputs="mic",
+    description="Let me try to guess what you're saying!",
+    hf_token=auth_token
+)
+
+demo.launch()