Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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Dataset with Mimi Codes

This dataset adds Mimi codec codes to parler-tts/libritts_r_filtered.

Dataset Description

Each sample contains:

audio: Audio resampled to 24kHz (Mimi's native rate)
codes: 8-layer Mimi codec codes (list of 8 lists of integers)
text: Text transcription (from text_normalized column)
Additional columns preserved from source dataset

Stats

Source: parler-tts/libritts_r_filtered
Splits: train.clean.360
Samples: 112,326
Audio Sample Rate: 24kHz
Codec: Mimi (kyutai/mimi) with 8 codebooks

Usage

from datasets import load_dataset

ds = load_dataset("mazesmazes/libritts-mimi", split="train")

# Access audio and codes together
sample = ds[0]
audio = sample["audio"]  # {'array': [...], 'sampling_rate': 24000}
codes = sample["codes"]  # 8 lists of codec indices
text = sample["text"]

# Decode codes back to audio
import torch
from transformers import MimiModel

mimi = MimiModel.from_pretrained("kyutai/mimi")
codes_tensor = torch.tensor(codes).unsqueeze(0)  # (1, 8, seq_len)
with torch.no_grad():
    decoded = mimi.decode(codes_tensor)
    waveform = decoded.audio_values  # (1, 1, samples) at 24kHz

Source Dataset

parler-tts/libritts_r_filtered

License

Same as source dataset.

Downloads last month: 38

Total file size:

93.7 GB