Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
_data_files: list<item: struct<filename: string>>
child 0, item: struct<filename: string>
child 0, filename: string
_fingerprint: string
_format_columns: null
_format_kwargs: struct<>
_format_type: null
_output_all_columns: bool
_split: string
embed: struct<vectormesh_version: string, model_tag: string, vectorizer_type: string, tensordtype: int64, h (... 96 chars omitted)
child 0, vectormesh_version: string
child 1, model_tag: string
child 2, vectorizer_type: string
child 3, tensordtype: int64
child 4, hidden_size: int64
child 5, context_size: null
child 6, stride: null
child 7, offsets_supported: null
child 8, chunk_sizes: null
created_at: string
num_observations: int64
features: list<item: string>
child 0, item: string
to
{'embed': {'vectormesh_version': Value('string'), 'model_tag': Value('string'), 'vectorizer_type': Value('string'), 'tensordtype': Value('int64'), 'hidden_size': Value('int64'), 'context_size': Value('null'), 'stride': Value('null'), 'offsets_supported': Value('null'), 'chunk_sizes': Value('null')}, 'features': List(Value('string')), 'created_at': Value('string'), 'num_observations': Value('int64')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
_data_files: list<item: struct<filename: string>>
child 0, item: struct<filename: string>
child 0, filename: string
_fingerprint: string
_format_columns: null
_format_kwargs: struct<>
_format_type: null
_output_all_columns: bool
_split: string
embed: struct<vectormesh_version: string, model_tag: string, vectorizer_type: string, tensordtype: int64, h (... 96 chars omitted)
child 0, vectormesh_version: string
child 1, model_tag: string
child 2, vectorizer_type: string
child 3, tensordtype: int64
child 4, hidden_size: int64
child 5, context_size: null
child 6, stride: null
child 7, offsets_supported: null
child 8, chunk_sizes: null
created_at: string
num_observations: int64
features: list<item: string>
child 0, item: string
to
{'embed': {'vectormesh_version': Value('string'), 'model_tag': Value('string'), 'vectorizer_type': Value('string'), 'tensordtype': Value('int64'), 'hidden_size': Value('int64'), 'context_size': Value('null'), 'stride': Value('null'), 'offsets_supported': Value('null'), 'chunk_sizes': Value('null')}, 'features': List(Value('string')), 'created_at': Value('string'), 'num_observations': Value('int64')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
fashion-mnist — mobilenet_v2_1.0_224 cache
Frozen embeddings of zalando-datasets/fashion_mnist, so you can train a head on a CPU laptop in seconds instead
of running an encoder over the images yourself.
Built for the MADS MachineLearning course.
| source dataset | zalando-datasets/fashion_mnist, revision 531be5e2ccc9dba0c201ad3ae567a4f3d16ecdd2 |
| encoder | google/mobilenet_v2_1.0_224, revision 75e607b00aeae1297cc89d026a118bce012f5c5a |
| hidden_size | 1280 |
| tensordtype | 1 |
| chunk_sizes | n/a — one vector per row |
| rows | 4.000 train / 1.000 test |
| columns | label, source_idx, embed |
| built with | vectormesh 0.4.1, 2026-08-01 |
The raw input column was dropped before upload — these are vectors and labels only.
Getting the original back
Rows carry a source_idx column: the row's position in the source split, so you can go from a
vector back to the image or text it came from without this repo having to carry it.
from datasets import load_dataset
source = load_dataset("zalando-datasets/fashion_mnist", revision="`531be5e2ccc9dba0c201ad3ae567a4f3d16ecdd2`")["train"]
source[train[5]["source_idx"]] # the original row behind cache row 5
Pass that revision. The cache was subsampled with a shuffle, so source_idx is not the row
number, and an index into a different revision of zalando-datasets/fashion_mnist would resolve to the wrong row
silently rather than failing.
Load it
from pathlib import Path
from huggingface_hub import snapshot_download
from vectormesh import VectorCache
path = Path(snapshot_download("pttrn-io/fashion-mnist-mobilenet_v2_1.0_224", repo_type="dataset"))
train = VectorCache.load(path / "train")
test = VectorCache.load(path / "test")
train.metadata # read this before writing any model code
This is a save_to_disk layout, not parquet: load_dataset() will not work on it,
VectorCache.load() will. For one split only, pass allow_patterns="train/*".
Licence
The embeddings inherit the terms of the source dataset, zalando-datasets/fashion_mnist. Cite it as its authors ask.
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