Datasets:

nsfwalex

/

checkpoint_n_lora

like 0

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 10 new columns ({'trainedWords', 'images', 'modelId', 'downloadCount', 'downloadUrl', 'model', 'name', 'id', 'files', 'createdAt'}) and 3 missing columns ({'checkpoint', 'lora', 'embedding'}).

This happened while the json dataset builder was generating data using

hf://datasets/nsfwalex/checkpoint_n_lora/lora/pony/style/DuaLipa.json (at revision 3b3f9466d030e7e30b8cffbcd693445742c99a73)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              id: int64
              modelId: int64
              name: string
              createdAt: string
              downloadUrl: string
              trainedWords: list<item: string>
                child 0, item: string
              model: struct<name: string, type: string, nsfw: bool>
                child 0, name: string
                child 1, type: string
                child 2, nsfw: bool
              files: list<item: struct<id: int64, sizeKB: double, name: string, type: string, pickleScanResult: string, pickleScanMessage: string, virusScanResult: string, virusScanMessage: null, scannedAt: string, metadata: struct<format: string>, hashes: struct<AutoV1: string, AutoV2: string, SHA256: string, CRC32: string, BLAKE3: string, AutoV3: string>, downloadUrl: string, primary: bool>>
                child 0, item: struct<id: int64, sizeKB: double, name: string, type: string, pickleScanResult: string, pickleScanMessage: string, virusScanResult: string, virusScanMessage: null, scannedAt: string, metadata: struct<format: string>, hashes: struct<AutoV1: string, AutoV2: string, SHA256: string, CRC32: string, BLAKE3: string, AutoV3: string>, downloadUrl: string, primary: bool>
                    child 0, id: int64
                    child 1, sizeKB: double
                    child 2, name: string
                    child 3, type: string
                    child 4, pickleScanResult: string
                    child 5, pickleScanMessage: string
                    child 6, virusScanResult: string
                    child 7, virusScanMessage: null
                    child 8, scannedAt: string
                    child 9, metadata: struct<format: string>
                        child 0, format: string
                    child 10, hashes: struct<AutoV1: string, AutoV2: string, SHA256: string, CRC32: string, BLAKE3: string, AutoV3: string>
                        child 0, AutoV1: string
                        child 1, AutoV2: string
                        child 2, SHA256: string
                        child 3, CRC32: string
                        child 4, BLAKE3: string
                        child 5, AutoV3: string
                    child 11, downloadUrl: string
                    child 12, primary: bool
              images: list<item: struct<url: string, nsfwLevel: int64, width: int64, height: int64, hash: string, type: string, hasMeta: bool, onSite: bool>>
                child 0, item: struct<url: string, nsfwLevel: int64, width: int64, height: int64, hash: string, type: string, hasMeta: bool, onSite: bool>
                    child 0, url: string
                    child 1, nsfwLevel: int64
                    child 2, width: int64
                    child 3, height: int64
                    child 4, hash: string
                    child 5, type: string
                    child 6, hasMeta: bool
                    child 7, onSite: bool
              downloadCount: int64
              to
              {'checkpoint': Sequence(feature=Value(dtype='null', id=None), length=-1, id=None), 'lora': [{'name': Value(dtype='string', id=None), 'path': Value(dtype='string', id=None), 'type': Value(dtype='string', id=None), 'attr': {'trigger_words': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'base_model': Value(dtype='string', id=None)}}], 'embedding': Sequence(feature=Value(dtype='null', id=None), length=-1, id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 10 new columns ({'trainedWords', 'images', 'modelId', 'downloadCount', 'downloadUrl', 'model', 'name', 'id', 'files', 'createdAt'}) and 3 missing columns ({'checkpoint', 'lora', 'embedding'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/nsfwalex/checkpoint_n_lora/lora/pony/style/DuaLipa.json (at revision 3b3f9466d030e7e30b8cffbcd693445742c99a73)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)