I hope this answers your question. Is there anything else I can help you with?Task Planning:1: {"task": "image-to-text", "id": 0, "dep": [-1], "args": {"image": "example.jpg"}}2: {"task": "text-to-speech", "id": 1, "dep": [0], "args": {"text": "<resource-1>"}Execution Results:1. {"generated text": "INVOICE NO : 18301/102/T0305"}Query: read the image example.jpg for me.Response: Sure. I have read the image         example.jpg for you. The inference result is 'INVOICE NO : 18301/102/T0305'. The model used for this task is        microsoft/trocr-base-printed, which is best suited for the task of image-to-text as it is fine-tuned on the SROIE dataset which is specifically designed for this task. Then I have converted the text to audio, the generated audio is        /audios/da5s.wav                                       and the model used for this task is        facebook/fastspeech2-en-ljspeech, which is a FastSpeech 2 text-to-speech model which is suitable for the task of text-to-speech.
HuggingGPT- Solving AI Tasks with ChatGPT and its Friends in Hugging Face