add link to fine-tuning example notebook

app.py

@@ -68,6 +68,8 @@ SpeechT5 can be fine-tuned for different speech tasks. This space demonstrates t
 See also the <a href="https://huggingface.co/spaces/Matthijs/speecht5-asr-demo">speech recognition (ASR) demo</a>
 and the <a href="https://huggingface.co/spaces/Matthijs/speecht5-vc-demo">voice conversion demo</a>.
 
+Refer to <a href="https://colab.research.google.com/drive/1i7I5pzBcU3WDFarDnzweIj4-sVVoIUFJ">this Colab notebook</a> to learn how to fine-tune the SpeechT5 TTS model on your own dataset or language.
+
 <b>How to use:</b> Enter some English text and choose a speaker. The output is a mel spectrogram, which is converted to a mono 16 kHz waveform by the
 HiFi-GAN vocoder. Because the model always applies random dropout, each attempt will give slightly different results.
 The <em>Surprise Me!</em> option creates a completely randomized speaker.