Datasets:

SpellcraftAI
/

wordnet

License:

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train

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The dataset generation failed

Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
similarity: double
word1: string
word2: string
-- schema metadata --
pandas: '{"index_columns": ["word1", "word2"], "column_indexes": [{"name"' + 551
to
{'part_of_speech': Value(dtype='string', id=None), 'embedding': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), 'word': Value(dtype='string', id=None)}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1492, in compute_config_parquet_and_info_response
                  fill_builder_info(builder, hf_endpoint=hf_endpoint, hf_token=hf_token, validate=validate)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 683, in fill_builder_info
                  ) = retry_validate_get_features_num_examples_size_and_compression_ratio(
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 602, in retry_validate_get_features_num_examples_size_and_compression_ratio
                  validate(pf)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 640, in validate
                  raise TooBigRowGroupsError(
              worker.job_runners.config.parquet_and_info.TooBigRowGroupsError: Parquet file has too big row groups. First row group has 469115268 which exceeds the limit of 300000000
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1995, in _prepare_split_single
                  for _, table in generator:
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 797, in wrapped
                  for item in generator(*args, **kwargs):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 97, in _generate_tables
                  yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 75, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              similarity: double
              word1: string
              word2: string
              -- schema metadata --
              pandas: '{"index_columns": ["word1", "word2"], "column_indexes": [{"name"' + 551
              to
              {'part_of_speech': Value(dtype='string', id=None), 'embedding': Sequence(feature=Value(dtype='float32', id=None), length=-1, id=None), 'word': Value(dtype='string', id=None)}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1505, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1099, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, 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 2038, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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part_of_speech string	embedding sequence	word string
v	[ -0.036610014736652374, -0.017415907233953476, 0.006714015267789364, -0.010407703928649426, -0.0208023339509964, 0.018069656565785408, -0.00911981612443924, -0.006844765041023493, 0.0018926069606095552, -0.027954360470175743, 0.018828008323907852, 0.01976940780878067, -0.01625223085284233, ...	hydrolyse
n	[ -0.009324440732598305, -0.01657070592045784, 0.0026472797617316246, -0.02094581164419651, -0.004440046846866608, 0.026250625029206276, -0.034180499613285065, -0.02253178507089615, 0.0015141961630433798, -0.0010493414010852575, 0.005315067712217569, 0.017992615699768066, 0.0027874198276549578...	eolith
a	[ 0.0015795731451362371, -0.02051074430346489, 0.00800761952996254, -0.0087240906432271, -0.018136555328965187, 0.03708792105317116, -0.0023654086980968714, -0.012770045548677444, -0.006676528602838516, -0.0038879099301993847, 0.019808322191238403, -0.00451306626200676, 0.004646526649594307, ...	accustomed
n	[ 0.007011003792285919, -0.03992515057325363, -0.0011138563277199864, -0.023322751745581627, -0.014348100870847702, 0.04480236768722534, -0.01290194783359766, -0.026612039655447006, -0.005823599174618721, -0.005554217845201492, 0.0173821859061718, 0.011689731851220131, -0.02142290584743023, ...	chooser
n	[ -0.026003817096352577, -0.021097971126437187, -0.009818780235946178, -0.015086183324456215, -0.01715628057718277, 0.03666623309254646, -0.006252826191484928, 0.0015756129287183285, -0.022473309189081192, -0.03799903392791748, 0.020474106073379517, 0.02414640039205551, 0.008556871674954891, ...	missive
a	[ -0.025289451703429222, 0.012184916995465755, 0.007086455821990967, -0.003610846819356084, -0.0051153660751879215, 0.00015161414921749383, -0.021056510508060455, -0.009135306812822819, -0.009933209046721458, -0.002824777504429221, 0.020245084539055824, 0.02948181889951229, 0.01129911001771688...	cylindric
n	[-0.006868151016533375,-0.0010382477194070816,0.012639538384974003,-0.0183239858597517,-0.0047916555(...TRUNCATED)	Glyceria
n	[-0.022798089310526848,-0.009078281000256538,-0.0029453220777213573,-0.020900525152683258,-0.0111533(...TRUNCATED)	equalisation
n	[0.005092069040983915,-0.015894735231995583,-0.0040276250801980495,-0.008314169012010098,-0.03184700(...TRUNCATED)	Putin
n,v	[0.015676984563469887,-0.003919246140867472,0.00961049273610115,-0.040276508778333664,-0.00787323806(...TRUNCATED)	chrome

End of preview.

This dataset contains the embeddings and cross cosine similarity for ~76k English nouns, verbs, and adjectives from Princeton's WordNet database.

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Total file size:

14 GB

Models trained or fine-tuned on SpellcraftAI/wordnet

kevinktg/GojoITSensei

Text Generation • Updated Sep 28, 2024