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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError Exception: UnicodeDecodeError Message: 'utf-8' codec can't decode byte 0x93 in position 0: invalid start byte Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 322, in compute compute_first_rows_from_parquet_response( File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 88, in compute_first_rows_from_parquet_response rows_index = indexer.get_rows_index( File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 640, in get_rows_index return RowsIndex( File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 521, in __init__ self.parquet_index = self._init_parquet_index( File "/src/libs/libcommon/src/libcommon/parquet_utils.py", line 538, in _init_parquet_index response = get_previous_step_or_raise( File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 591, in get_previous_step_or_raise raise CachedArtifactError( libcommon.simple_cache.CachedArtifactError: The previous step failed. 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/packaged_modules/json/json.py", line 122, in _generate_tables pa_table = paj.read_json( File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 240, in compute_first_rows_from_streaming_response iterable_dataset = iterable_dataset._resolve_features() File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2216, in _resolve_features features = _infer_features_from_batch(self.with_format(None)._head()) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1239, in _head return _examples_to_batch(list(self.take(n))) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1389, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1044, in __iter__ yield from islice(self.ex_iterable, self.n) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 282, in __iter__ for key, pa_table in self.generate_tables_fn(**self.kwargs): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 145, in _generate_tables dataset = json.load(f) File "/usr/local/lib/python3.9/json/__init__.py", line 293, in load return loads(fp.read(), File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1104, in read_with_retries out = read(*args, **kwargs) File "/usr/local/lib/python3.9/codecs.py", line 322, in decode (result, consumed) = self._buffer_decode(data, self.errors, final) UnicodeDecodeError: 'utf-8' codec can't decode byte 0x93 in position 0: invalid start byte
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This dataset contains the embeddings for the segmented TREC RAG 2024 corpus, embedded with the Cohere Embed V3 model.
You can search on this dataset with just 500MB of memory using DiskVectorIndex.
Installation & Usage
Get your free Cohere API key from cohere.com. You must set this API key as an environment variable:
export COHERE_API_KEY=your_api_key
Install the package:
pip install DiskVectorIndex
You can then search via:
from DiskVectorIndex import DiskVectorIndex
index = DiskVectorIndex("Cohere/trec-rag-2024-index")
while True:
query = input("\n\nEnter a question: ")
docs = index.search(query, top_k=3)
for doc in docs:
print(doc)
print("=========")
License
Please observe the License for the TREC RAG 2024 Corpus. The license displayed here is just for the embeddings.
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