lap-htsat-unfused")
        >>> processor = AutoProcessor.from_pretrained("laion/clap-htsat-unfused")

        >>> input_text = ["Sound of a dog", "Sound of vaccum cleaner"]

        >>> inputs = processor(text=input_text, audios=audio_sample, return_tensors="pt", padding=True)

        >>> outputs = model(**inputs)
        >>> logits_per_audio = outputs.logits_per_audio  # this is the audio-text similarity score
        >>> probs = logits_per_audio.softmax(dim=-1)  # we can take the softmax to get the label probabilities
        ```Nr¨