limit q and link to repo

app.py

@@ -13,12 +13,12 @@ from transformers.pipelines.audio_utils import ffmpeg_read
 
 title = "Whisper JAX: The Fastest Whisper API ⚡️"
 
-description = "Whisper JAX is an optimised implementation of the [Whisper model](https://huggingface.co/openai/whisper-large-v2) by OpenAI. It runs on JAX with a TPU v4-8 in the backend. Compared to PyTorch on an A100 GPU, it is over **70x** faster, making it the fastest Whisper API available."
+description = "Whisper JAX is an optimised implementation of the [Whisper model](https://huggingface.co/openai/whisper-large-v2) by OpenAI. It runs on JAX with a TPU v4-8 in the backend. Compared to PyTorch on an A100 GPU, it is over [**70x** faster](https://github.com/sanchit-gandhi/whisper-jax#benchmarks), making it the fastest Whisper API available."
 
 API_URL = os.getenv("API_URL")
 API_URL_FROM_FEATURES = os.getenv("API_URL_FROM_FEATURES")
 
-article = "Whisper large-v2 model by OpenAI. Backend running JAX on a TPU v4-8 through the generous support of the [TRC](https://sites.research.google/trc/about/) programme. Whisper JAX code and Gradio demo by 🤗 Hugging Face."
+article = "Whisper large-v2 model by OpenAI. Backend running JAX on a TPU v4-8 through the generous support of the [TRC](https://sites.research.google/trc/about/) programme. Whisper JAX [code](https://github.com/sanchit-gandhi/whisper-jax) and Gradio demo by 🤗 Hugging Face."
 
 language_names = sorted(TO_LANGUAGE_CODE.keys())
 CHUNK_LENGTH_S = 30
@@ -161,5 +161,5 @@ if __name__ == "__main__":
     with demo:
         gr.TabbedInterface([audio_chunked, youtube], ["Transcribe Audio", "Transcribe YouTube"])
 
-    demo.queue()
+    demo.queue(max_size=10)
     demo.launch()