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The JWT signature verification failed. Check the signing key and the algorithm.
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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AutoTrain Dataset for project: multifamily_v2

Dataset Description

This dataset has been automatically processed by AutoTrain for project multifamily_v2.

Languages

The BCP-47 code for the dataset's language is unk.

Dataset Structure

Data Instances

A sample from this dataset looks as follows:

[
  {
    "image": "<500x333 RGB PIL image>",
    "target": 33
  },
  {
    "image": "<500x667 RGB PIL image>",
    "target": 11
  }
]

Dataset Fields

The dataset has the following fields (also called "features"):

{
  "image": "Image(decode=True, id=None)",
  "target": "ClassLabel(names=['Balcony-Patio', 'Bathroom', 'Bedroom', 'Bike', 'Building', 'Business Center', 'Business Center Conference Room', 'Closet', 'Clubhouse', 'Clubhouse Dining Room', 'Construction', 'Dining Room', 'Dog Park', 'Fire Pit', 'Fitness Center', 'Floorplan', 'Fountain', 'Green Space', 'Grilling Area', 'Hallway', 'Headshot', 'Home Office', 'Hot Tub', 'Kitchen', 'Laundry Facility', 'Laundry Washer-Dryer', 'Leasing Office', 'Living Room', 'Living Room Fireplace', 'Logo', 'Lounge Area', 'Mail Box', 'Monument Sign', 'Neighborhood', 'Packages', 'Parking', 'Pet Washing', 'Picnic Area', 'Play Park', 'Pool', 'Pool Cabanas', 'Pool Table', 'Private Garage', 'Site-plan', 'Stock Photo', 'Tennis Court', 'View-Aerial', 'room'], id=None)"
}

Dataset Splits

This dataset is split into a train and validation split. The split sizes are as follow:

Split name Num samples
train 1748
valid 453
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Models trained or fine-tuned on lineups-io/autotrain-data-multifamily_v2