Load a processor with [AutoProcessor.from_pretrained]:

from transformers import AutoProcessor
processor = AutoProcessor.from_pretrained("facebook/wav2vec2-base-960h")

Create a function to process the audio data contained in array to input_values, and tokenize text to labels. These are the inputs to the model:

def prepare_dataset(example):
     audio = example["audio"]

     example.update(processor(audio=audio["array"], text=example["text"], sampling_rate=16000))
     return example