add colab link

README.md

@@ -134,30 +134,11 @@ afrispeech = load_dataset("tobiolatunji/afrispeech-200", "isizulu", split="train
 dataloader = DataLoader(afrispeech, batch_size=32)
 ```
 
-To find out more about loading and preparing audio datasets, head over to [hf.co/blog/audio-datasets](https://huggingface.co/blog/audio-datasets).
 
-### Example scripts
+### Fine-tuning Colab tutorial
 
-Train your own CTC or Seq2Seq Automatic Speech Recognition models on AfriSpeech-200 with `transformers` - [here](https://github.com/huggingface/transformers/tree/main/examples/pytorch/speech-recognition).
+To walk through a complete colab tutorial that finetunes a wav2vec2 model on the afrispeech-200 dataset with `transformers`, take a look at this colab notebook [afrispeech/wav2vec2-colab-tutorial](https://colab.research.google.com/drive/1uZYew6pcgN6UE6sFDLohxD_HKivvDXzD?usp=sharing#scrollTo=_UEjJqGsQw24).
 
-AfriSpeech-200 can be downloaded and used as follows:
-
-```py
-from datasets import load_dataset
-
-afrispeech = load_dataset("tobiolatunji/afrispeech-200", "isizulu") # for isizulu, 
-# to download all data for multi-accent fine-tuning uncomment following line
-# afrispeech = load_dataset("tobiolatunji/afrispeech-200", "all")
-
-# see structure
-print(afrispeech)
-
-# load audio sample on the fly
-audio_input = afrispeech["train"][0]["audio"]  # audio bytes
-transcript = afrispeech["train"][0]["transcript"]  # transcript
-
-# use audio_input and text transcript to fine-tune your model for audio classification
-```
 
 ### Supported Tasks and Leaderboards