hubert-sd /
Narsil's picture
HF staff
This is just an example of what people would submit for inference.
import os
from typing import Dict, List
import torch
from s3prl.downstream.runner import Runner
class PreTrainedModel(Runner):
def __init__(self, path=""):
Initialize downstream model.
ckp_file = os.path.join(path, "hubert_sd.ckpt")
ckp = torch.load(ckp_file, map_location="cpu")
ckp["Args"].init_ckpt = ckp_file
ckp["Args"].mode = "inference"
ckp["Args"].device = "cpu" # Just to try in my computer
Runner.__init__(self, ckp["Args"], ckp["Config"])
def __call__(self, inputs) -> List[int]:
Args: inputs (:obj:`np.array`): The raw waveform of audio received. By
default at 16KHz.
Return: A list with logits.
for entry in self.all_entries:
inputs = [torch.FloatTensor(inputs)]
with torch.no_grad():
features = self.upstream.model(inputs)
features = self.featurizer.model(inputs, features)
preds = self.downstream.model.inference(features, [])
return preds[0]
import io
import soundfile as sf
from urllib.request import urlopen
model = PreTrainedModel()
url = ""
data, samplerate =