from typing import Dict, List, Any | |
from transformers import pipeline | |
class EndpointHandler: | |
def __init__(self, path=""): | |
self.model = pipeline("text-to-speech", "suno/bark") | |
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]: | |
""" | |
data args: | |
inputs (:obj: `str`) | |
date (:obj: `str`) | |
Return: | |
A :obj:`list` | `dict`: will be serialized and returned | |
""" | |
# get inputs | |
text_prompt = data.pop("inputs", data) | |
# run normal prediction | |
speech_array = self.model(text_prompt,forward_params={"do_sample": True}) | |
return speech_array | |