AceRAG
Collection
Ad-hoc Context Compression for RAG • 3 items • Updated
• 1
Dataset Preview
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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 ({'label', 'text', 'input', 'all_classes'}) and 6 missing columns ({'key_index', 'key', 'answerKey', 'id', 'question', 'choices'}).
This happened while the json dataset builder was generating data using
hf://datasets/wcyno23/AceRAG-Data/train/context_compressor/banking77.json (at revision 772282fb380a4778bf3adb2162229519408de74c), ['hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/arc_challenge.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/arc_easy.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/banking77.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/gov_report.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/hotpotqa.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/longalpaca.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/multi_news.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/nq.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/redpajama.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/trec_fine.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/arc_challenge_llama2.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/arc_challenge_qwen3.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/gov_report_llama2.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/gov_report_qwen3.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/hotpotqa_llama2.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/hotpotqa_qwen3.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/multi_news_llama2.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/multi_news_qwen3.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/nq_llama2.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/nq_qwen3.json']
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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 675, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
text: string
label: int64
all_classes: list<item: string>
child 0, item: string
answers: list<item: string>
child 0, item: string
query: string
input: string
conversations: list<item: struct<content: string, context: string, prompt: string, role: string>>
child 0, item: struct<content: string, context: string, prompt: string, role: string>
child 0, content: string
child 1, context: string
child 2, prompt: string
child 3, role: string
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 925
to
{'id': Value('string'), 'question': Value('string'), 'choices': {'text': List(Value('string')), 'label': List(Value('string'))}, 'answerKey': Value('string'), 'query': Value('string'), 'answers': List(Value('string')), 'key': List(Value('string')), 'key_index': List(Value('int64')), 'conversations': List({'content': Value('string'), 'context': Value('string'), 'prompt': Value('string'), 'role': Value('string')})}
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 1342, 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 907, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1889, 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 ({'label', 'text', 'input', 'all_classes'}) and 6 missing columns ({'key_index', 'key', 'answerKey', 'id', 'question', 'choices'}).
This happened while the json dataset builder was generating data using
hf://datasets/wcyno23/AceRAG-Data/train/context_compressor/banking77.json (at revision 772282fb380a4778bf3adb2162229519408de74c), ['hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/arc_challenge.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/arc_easy.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/banking77.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/gov_report.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/hotpotqa.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/longalpaca.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/multi_news.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/nq.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/redpajama.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/context_compressor/trec_fine.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/arc_challenge_llama2.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/arc_challenge_qwen3.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/gov_report_llama2.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/gov_report_qwen3.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/hotpotqa_llama2.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/hotpotqa_qwen3.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/multi_news_llama2.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/multi_news_qwen3.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/nq_llama2.json', 'hf://datasets/wcyno23/AceRAG-Data@772282fb380a4778bf3adb2162229519408de74c/train/token_level_estimator/nq_qwen3.json']
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.
id string | question string | choices dict | answerKey string | query string | answers list | key list | key_index list | conversations list |
|---|---|---|---|---|---|---|---|---|
Mercury_SC_415702 | George wants to warm his hands quickly by rubbing them. Which skin surface will produce the most heat? | {
"text": [
"dry palms",
"wet palms",
"palms covered with oil",
"palms covered with lotion"
],
"label": [
"A",
"B",
"C",
"D"
]
} | A | George wants to warm his hands quickly by rubbing them. Which skin surface will produce the most heat? Answer Choices: A: dry palms B: wet palms C: palms covered with oil D: palms covered with lotion | [
"A"
] | [
"Keratolysis exfoliativa Keratolysis exfoliativa\nKeratolysis exfoliativa (also known as \"lamellar dyshidrosis\", \"recurrent focal palmar peeling\", \"recurrent palmar peeling\") is a sometimes harmless, sometimes painful skin condition that can affect the focal surface of the fingers and/or the palm or soles of ... | [
3545975,
1176035,
2962186,
5180276,
3337250
] | [
{
"content": "Answer the question based on the given documents. Only give me the answer and do not output any other words.\n\nThe following are given documents.\nDoc 1: Keratolysis exfoliativa Keratolysis exfoliativa\nKeratolysis exfoliativa (also known as \"lamellar dyshidrosis\", \"recurrent focal palmar peel... |
MCAS_2009_5_6516 | Which of the following statements best explains why magnets usually stick to a refrigerator door? | {
"text": [
"The refrigerator door is smooth.",
"The refrigerator door contains iron.",
"The refrigerator door is a good conductor.",
"The refrigerator door has electric wires in it."
],
"label": [
"A",
"B",
"C",
"D"
]
} | B | Which of the following statements best explains why magnets usually stick to a refrigerator door? Answer Choices: A: The refrigerator door is smooth. B: The refrigerator door contains iron. C: The refrigerator door is a good conductor. D: The refrigerator door has electric wires in it. | [
"B"
] | [
"Magnet Magnet\nA magnet is a material or object that produces a magnetic field. This magnetic field is invisible but is responsible for the most notable property of a magnet: a force that pulls on other ferromagnetic materials, such as iron, and attracts or repels other magnets. \nA permanent magnet is an object m... | [
1527429,
3026221,
5113476,
2486424,
3216324
] | [
{
"content": "Answer the question based on the given documents. Only give me the answer and do not output any other words.\n\nThe following are given documents.\nDoc 1: Magnet Magnet\nA magnet is a material or object that produces a magnetic field. This magnetic field is invisible but is responsible for the mos... |
Mercury_7233695 | A fold observed in layers of sedimentary rock most likely resulted from the | {
"text": [
"cooling of flowing magma.",
"converging of crustal plates.",
"deposition of river sediments.",
"solution of carbonate minerals."
],
"label": [
"A",
"B",
"C",
"D"
]
} | B | A fold observed in layers of sedimentary rock most likely resulted from the Answer Choices: A: cooling of flowing magma. B: converging of crustal plates. C: deposition of river sediments. D: solution of carbonate minerals. | [
"B"
] | [
"Fold (geology) Fold (geology)\nIn structural geology, folds occur when one or a stack of originally flat and planar surfaces, such as sedimentary strata, are bent or curved as a result of permanent deformation. Synsedimentary folds are those due to slumping of sedimentary material before it is lithified. Folds in ... | [
444879,
1788669,
3865310,
5054654,
3281959
] | [
{
"content": "Answer the question based on the given documents. Only give me the answer and do not output any other words.\n\nThe following are given documents.\nDoc 1: Fold (geology) Fold (geology)\nIn structural geology, folds occur when one or a stack of originally flat and planar surfaces, such as sedimenta... |
Mercury_7041615 | Which of these do scientists offer as the most recent explanation as to why many plants and animals died out at the end of the Mesozoic era? | {
"text": [
"worldwide disease",
"global mountain building",
"rise of mammals that preyed upon plants and animals",
"impact of an asteroid created dust that blocked the sunlight"
],
"label": [
"A",
"B",
"C",
"D"
]
} | D | Which of these do scientists offer as the most recent explanation as to why many plants and animals died out at the end of the Mesozoic era? Answer Choices: A: worldwide disease B: global mountain building C: rise of mammals that preyed upon plants and animals D: impact of an asteroid created dust that blocked the sunlight | [
"D"
] | [
"Mesozoic Mesozoic\nThe Mesozoic Era ( or ) is an interval of geological time from about . It is also called the Age of Reptiles and the Age of Conifers.\nThe Mesozoic (\"middle life\") is one of three geologic eras of the Phanerozoic Eon, preceded by the Paleozoic (\"ancient life\") and succeeded by the Cenozoic (... | [
5175330,
1578929,
1461605,
2708759,
1294809
] | [
{
"content": "Answer the question based on the given documents. Only give me the answer and do not output any other words.\n\nThe following are given documents.\nDoc 1: Mesozoic Mesozoic\nThe Mesozoic Era ( or ) is an interval of geological time from about . It is also called the Age of Reptiles and the Age of ... |
Mercury_7041860 | "A boat is acted on by a river current flowing north and by wind blowing on its sails. The boat trav(...TRUNCATED) | {
"text": [
"west",
"east",
"north",
"south"
],
"label": [
"A",
"B",
"C",
"D"
]
} | B | "A boat is acted on by a river current flowing north and by wind blowing on its sails. The boat trav(...TRUNCATED) | [
"B"
] | ["Forces on sails Forces on sails\nForces on sails result from movement of air that interacts with s(...TRUNCATED) | [
4883236,
3045542,
148444,
496482,
496476
] | [{"content":"Answer the question based on the given documents. Only give me the answer and do not ou(...TRUNCATED) |
Mercury_SC_401653 | Which land form is the result of the constructive force of a glacier? | {"text":["valleys carved by a moving glacier","piles of rocks deposited by a melting glacier","groov(...TRUNCATED) | B | "Which land form is the result of the constructive force of a glacier? Answer Choices: A: valleys ca(...TRUNCATED) | [
"B"
] | ["Glacial landform Glacial landform\nGlacial landforms are landforms created by the action of glacie(...TRUNCATED) | [
2658063,
3750799,
1289595,
1308789,
254341
] | [{"content":"Answer the question based on the given documents. Only give me the answer and do not ou(...TRUNCATED) |
MEA_2016_8_14 | Which statement best compares single-celled and multi-celled organisms? | {"text":["Tissues in a single-celled organism are like the cells in a multi-celled organism.","The n(...TRUNCATED) | C | "Which statement best compares single-celled and multi-celled organisms? Answer Choices: A: Tissues (...TRUNCATED) | [
"C"
] | ["Organism Organism\nIn biology, an organism (from Greek: ὀργανισμός, \"organismos\") is (...TRUNCATED) | [
3993203,
2476009,
977923,
900439,
3885201
] | [{"content":"Answer the question based on the given documents. Only give me the answer and do not ou(...TRUNCATED) |
ACTAAP_2013_5_11 | "As part of an experiment, an astronaut takes a scale to the Moon and weighs himself. The scale read(...TRUNCATED) | {"text":["31 pounds and 14 kilograms","31 pounds and 84 kilograms","186 pounds and 14 kilograms","18(...TRUNCATED) | D | "As part of an experiment, an astronaut takes a scale to the Moon and weighs himself. The scale read(...TRUNCATED) | [
"D"
] | ["Apparent weight Apparent weight\nIn physics, apparent weight is a property of objects that corresp(...TRUNCATED) | [
467646,
2718724,
3706973,
3966895,
2223761
] | [{"content":"Answer the question based on the given documents. Only give me the answer and do not ou(...TRUNCATED) |
MCAS_1998_4_3 | Which of the following is a trait that a dog does NOT inherit from its parents? | {"text":["the length of its fur","the shape of its nose","the size of its appetite","the color of it(...TRUNCATED) | C | "Which of the following is a trait that a dog does NOT inherit from its parents? Answer Choices: A: (...TRUNCATED) | [
"C"
] | ["Phenotypic trait Phenotypic trait\nA phenotypic trait, simply trait, or character state is a disti(...TRUNCATED) | [
3268972,
3342389,
581947,
5436284,
2668183
] | [{"content":"Answer the question based on the given documents. Only give me the answer and do not ou(...TRUNCATED) |
Mercury_7106908 | "Hatchling sea turtles are typically dark in color. Occasionally, a sea turtle hatches that is almos(...TRUNCATED) | {"text":["help the turtles have better chances at reproducing.","cause the shell of the sea turtles (...TRUNCATED) | C | "Hatchling sea turtles are typically dark in color. Occasionally, a sea turtle hatches that is almos(...TRUNCATED) | [
"C"
] | ["Threats to sea turtles Threats to sea turtles\nThreats to sea turtles are numerous and have caused(...TRUNCATED) | [
3699186,
2543390,
5143053,
4137037,
3868661
] | [{"content":"Answer the question based on the given documents. Only give me the answer and do not ou(...TRUNCATED) |
End of preview.
AceRAG
Introduction
AceRAG provides task-aware context compression that transforms lengthy prompts into compact representations while preserving task-critical information. Designed for retrieval-augmented generation (RAG) systems, it employs a task-aware compressor and a compression-rate adapter to dynamically emphasize important tokens according to the task.
Dataset Directory Structure
AceRAG-Data/
├── train/ # Training set
│ ├── context_compressor/ # Context compressor training data
│ └── token_level_estimator/ # Token-level estimator training data
└── eval/ # Evaluation set
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