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The dataset generation failed because of a cast error
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 4 new columns ({'dimensions', 'video_name', 'video_type', 'question'}) and 2 missing columns ({'org_index', 'answer'}).
This happened while the json dataset builder was generating data using
hf://datasets/opencompass/MMBench-Video/MMBench-Video_q.json (at revision 53b6cef24b62aadda40b4144e6c11ea824882d6c)
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 1869, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 580, 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
video_name: string
question_id: string
question: string
dimensions: string
video_type: string
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 718
to
{'answer': Value(dtype='string', id=None), 'org_index': Value(dtype='int64', id=None), 'question_id': Value(dtype='string', 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 1387, 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 980, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1740, 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 1871, 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 4 new columns ({'dimensions', 'video_name', 'video_type', 'question'}) and 2 missing columns ({'org_index', 'answer'}).
This happened while the json dataset builder was generating data using
hf://datasets/opencompass/MMBench-Video/MMBench-Video_q.json (at revision 53b6cef24b62aadda40b4144e6c11ea824882d6c)
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)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
answer
string | org_index
int64 | question_id
string |
|---|---|---|
Palmer. | 0 | wZxzBvAgqxc_0 |
3 | 1 | wZxzBvAgqxc_1 |
Yes. The second goal in the video was originally shot by a Red team player, but the Blue team defenseman knocked the ball into his own goal. | 2 | wZxzBvAgqxc_2 |
This video is a key moments replay of a football game. The team in red jerseys scored two goals, and the team in blue jerseys scored one goal. | 3 | wZxzBvAgqxc_3 |
Paypal honey | 4 | lKNB3ZeTYiI_processed_0 |
sound-proofing earmuffs | 5 | lKNB3ZeTYiI_processed_1 |
It helps you save money when shopping online! | 6 | lKNB3ZeTYiI_processed_2 |
He was improving some item recipes in the game Minecraft. | 7 | 4jOk3ajqJ2s_processed_0 |
Because the output of the original recipe is really annoying. | 8 | 4jOk3ajqJ2s_processed_1 |
In the improved recipe, each stone block yields 72 stone buttons, therefore, 5 stone blocks yield 360. (5 x 72 = 360) | 9 | 4jOk3ajqJ2s_processed_2 |
There is no way to know based on the video content. | 10 | 4jOk3ajqJ2s_processed_3 |
7 | 11 | rtfS6PQEot0_0 |
It's called "We Are More". | 12 | rtfS6PQEot0_1 |
Because other champions can block the impact of her charge. | 13 | rtfS6PQEot0_2 |
Shurima | 14 | rtfS6PQEot0_3 |
The name of the person that started the vote is no longer revealed. | 15 | qsqGAaEV3lw_0 |
He/she will not be able to start a vote, since a player can't initiate 2 votes within 6 minutes. | 16 | qsqGAaEV3lw_1 |
It will automatically close. | 17 | qsqGAaEV3lw_2 |
I don't know, since there are only 4 points mentioned in the video. | 18 | qsqGAaEV3lw_3 |
It's called "Royal Maelstrom". | 19 | lZC0QV4N3OU_processed_0 |
4 | 20 | lZC0QV4N3OU_processed_1 |
Once has filled her stomach and assumed her ture form (after using R). | 21 | lZC0QV4N3OU_processed_2 |
I don't know, since there are only 5 ability mentioned in the video. | 22 | lZC0QV4N3OU_processed_3 |
Tranquilizer Rifle and Steel net gun. | 23 | 6MSJsDyFxcQ_0 |
Sushi and Seafood Cuisine | 24 | 6MSJsDyFxcQ_1 |
Seahorses | 25 | 6MSJsDyFxcQ_2 |
It was on fire. | 26 | 5zCc934KAi0_0 |
He jumped into the straw. | 27 | 5zCc934KAi0_1 |
An assassin or a warrior. | 28 | 5zCc934KAi0_2 |
He used a bow and arrow. | 29 | hSZLHJRZUOg_processed_0 |
There is no way to know based on the video content. | 30 | hSZLHJRZUOg_processed_1 |
19.3 tonnes | 31 | ZRrYCyEc9_M_0 |
A single airplane. | 32 | ZRrYCyEc9_M_1 |
Because you can milk an infinite amount of milk out of a cow, and the cow needs nothing to produce it. | 33 | ZRrYCyEc9_M_2 |
Cleaning Master and Drinking Serving Master | 34 | vTxcVxD3Uk0_0 |
17101 | 35 | vTxcVxD3Uk0_1 |
825 | 36 | vTxcVxD3Uk0_2 |
Winter. | 37 | aR-KAldshAE_0 |
A pair of metal gloves. | 38 | aR-KAldshAE_1 |
League of Legends | 39 | aR-KAldshAE_2 |
Poseidon's Trident | 40 | vNFSIHdsMT8_processed_0 |
A actual working plane. | 41 | Ak1eEUNrpgo_processed_0 |
Four. | 42 | Ak1eEUNrpgo_processed_1 |
There is no way to know based on the video content. | 43 | Ak1eEUNrpgo_processed_2 |
Green. | 44 | Uq9jqhSOUQQ_0 |
Bandito. | 45 | Uq9jqhSOUQQ_1 |
There is no way to know based on the video content. | 46 | Uq9jqhSOUQQ_2 |
Pink or purple | 47 | hIyrb8PeGXs_0 |
Poison. | 48 | hIyrb8PeGXs_1 |
There is no way to know based on the video content. | 49 | hIyrb8PeGXs_2 |
It can break through floors and wooden doors. | 50 | Qnyb73rf7gM_processed_0 |
4 | 51 | Qnyb73rf7gM_processed_1 |
Red. | 52 | Qnyb73rf7gM_processed_2 |
There is no way to know based on the video content. | 53 | Qnyb73rf7gM_processed_3 |
A tower. | 54 | ka5t4Msfras_0 |
A helicopter | 55 | ka5t4Msfras_1 |
Yes, it's a woman. | 56 | ka5t4Msfras_2 |
Kitchen. | 57 | LqNCz7q0bf4_processed_0 |
Sunrise Bar. | 58 | LqNCz7q0bf4_processed_1 |
League of Legends and Minecraft. | 59 | dSHcCllTCzY_0 |
It's a good bet that it is. | 60 | dSHcCllTCzY_1 |
125 | 61 | 9mKJtnY3qgQ_processed_0 |
Red. | 62 | 9mKJtnY3qgQ_processed_1 |
07:42.7 | 63 | X-miELlaEYw_0 |
Realme | 64 | UBV5mJuJ1xg_0 |
Liu Chuanzhi | 65 | UBV5mJuJ1xg_1 |
Wiko | 66 | UBV5mJuJ1xg_2 |
Nokia | 67 | SvUHeoFtSKw_0 |
2 | 68 | SvUHeoFtSKw_1 |
Smooth user experience; 3 days battery life; quick fix self-repair; 100% recycled plastic back; AI camera; refined audio. | 69 | SvUHeoFtSKw_2 |
There is no way to know based on the video content. | 70 | SvUHeoFtSKw_3 |
Samsung | 71 | y0ozEcgchhw_0 |
1 | 72 | y0ozEcgchhw_1 |
The 2nd place | 73 | y0ozEcgchhw_2 |
The Next Applied | 74 | HtFrFZN8ud4_0 |
HCL Technologies. | 75 | HtFrFZN8ud4_1 |
Mindtree. | 76 | HtFrFZN8ud4_2 |
He wears an electronic watch on his left hand. | 77 | ZuqdsI5hNJ4_0 |
No. He wears myopia glasses. | 78 | ZuqdsI5hNJ4_1 |
He is Li Ka-shing | 79 | ZuqdsI5hNJ4_2 |
There are three important reasons for this.
1. Economic growth is now well ahead of the Fed’s long-term potential growth rate.
2. Expansion of the government deficit and investment in clean energy may increase the demand for saving and push up the neutral interest rate.
3. Retirees in industrial economies may be spending those savings now. | 80 | Y2gLmboNrKk_0 |
This reveals an important turning point in the global economy from a prolonged low interest rate environment to a possible era of higher interest rates. | 81 | Y2gLmboNrKk_1 |
Yes. The dollar bills appear around the 21s of the video. | 82 | Y2gLmboNrKk_2 |
Before that, they need to open the vaccine pass and scan the code to enter. | 83 | wfQlSw2zeZk_0 |
The reasons for their absence were schedule conflicts or COVID-19 infection, but some media believed that they had received pressure from the US government. | 84 | wfQlSw2zeZk_1 |
Her coat is pink. | 85 | lnShWOBzgGM_0 |
The Republican Party criticized the Biden administration for waste. | 86 | lnShWOBzgGM_1 |
Biden unveils taxes and gets paid less than last year. | 87 | lnShWOBzgGM_2 |
The banking sector's share price index rose 2.92% | 88 | DsCMMJTCGk4_0 |
Her occupation is a commentator for Securities Daily. | 89 | DsCMMJTCGk4_1 |
This video talks about the knowledge of stock trading. | 90 | akJ6MPa7ujs_0 |
he was wearing a gray baseball cap. | 91 | akJ6MPa7ujs_1 |
26.00 | 92 | akJ6MPa7ujs_2 |
This video talks about experiences about stock trading. | 93 | ODzyaMRExpA_0 |
No. The book is placed under the globe. | 94 | ODzyaMRExpA_1 |
He is 46 years old. | 95 | gNBg3wqo_cM_0 |
An artist is suspected of having counterfeit NT$500 banknotes on the market. The artist specializes in making counterfeit banknotes and sells them. The studio turns into a counterfeit banknote manufacturing factory. | 96 | gNBg3wqo_cM_1 |
Counterfeit banknotes are not saturated in color and smooth to the touch. | 97 | gNBg3wqo_cM_2 |
She wears a red coat. | 98 | YdySNuZSh4Y_0 |
Interest rates surge, S&P warns of rising debt default risks for Latin American companies | 99 | YdySNuZSh4Y_1 |
End of preview.