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kai_synth_v1

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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:    ValueError
Message:      Invalid string class label kai_synth_v1@fb7bae85f3690bf0e761714c0ab57805a0aebdad
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 544, 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 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2572, in __iter__
                  example = _apply_feature_types_on_example(
                      example, self.features, token_per_repo_id=self.token_per_repo_id
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2489, in _apply_feature_types_on_example
                  encoded_example = features.encode_example(example)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2244, in encode_example
                  return encode_nested_example(self, example)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1518, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                      ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1541, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                         ~~~~~~~~~~~~~~~~~~~~~^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1210, in encode_example
                  example_data = self.str2int(example_data)
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1147, in str2int
                  output = [self._strval2int(value) for value in values]
                            ~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1168, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label kai_synth_v1@fb7bae85f3690bf0e761714c0ab57805a0aebdad

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K-Ai Synth v1

An Open Dataset by K-Ai

K-Ai Synth v1 is an openly available dataset developed and maintained by K-Ai (Kortex AI) to support the development, training, fine-tuning, and evaluation of AI models.

The dataset is part of K-Ai's effort to build an accessible AI development ecosystem, providing data resources for K-Ai models and the wider machine learning community.

Our goal is not only to develop models within K-Ai, but also to make useful resources available to developers, researchers, students, and independent AI builders.

About the Dataset

K-Ai Synth v1 is designed to serve as a shared dataset resource across the K-Ai model ecosystem.

It can be used in different stages of model development, including:

  • Pre-training and continued training.
  • Supervised fine-tuning (SFT).
  • Instruction tuning.
  • Model experimentation and research.
  • Dataset evaluation and benchmarking.
  • Development of independent AI projects.

The dataset is intended to support the continuous improvement of K-Ai models and encourage broader experimentation within the open AI community.

Created for K-Ai Models

This dataset is developed as part of the K-Ai ecosystem and may be used in the development of various K-Ai models.

It is not restricted to a single model or architecture.

K-Ai models may use this dataset as part of their training or fine-tuning pipelines, depending on their individual requirements and compatibility.

Open for Public Use

K-Ai Synth v1 is not exclusively reserved for K-Ai.

We welcome the wider AI community to explore and use this dataset.

Potential users include:

  • AI developers and researchers.
  • Independent model creators.
  • Students and educational projects.
  • Open-source AI communities.
  • Organizations experimenting with machine learning.

You may use, modify, and redistribute the dataset under the terms of the Apache License 2.0.

Please review the license and respect any applicable rights and conditions associated with individual data sources.

License

This dataset is released under the Apache License 2.0.

You are permitted to:

  • Use the dataset for personal and commercial projects.
  • Modify and adapt the dataset.
  • Use it for training and fine-tuning AI models.
  • Redistribute original or modified versions.

Please retain applicable copyright notices, license information, and required notices when redistributing the dataset.

See the "Apache License 2.0" (https://www.apache.org/licenses/LICENSE-2.0) for the complete terms.

Dataset Information

Property| Details Dataset Name| K-Ai Synth v1 Organization| K-Ai (Kortex AI) Repository| K-Ai-Official/kai_synth_v1 Version| 1.0 License| Apache 2.0 Availability| Public Intended Use| AI training, fine-tuning, research, and experimentation

Responsible Use

Users are encouraged to:

  • Review the dataset before using it.
  • Validate data quality for their intended application.
  • Evaluate models trained with this dataset.
  • Follow responsible AI development practices.
  • Respect the rights and licenses of any referenced data sources.

K-Ai does not guarantee that models trained using this dataset will achieve a particular performance level.

About K-Ai

K-Ai (Kortex AI) is an independent AI development initiative focused on building AI models, tools, and accessible infrastructure.

Our philosophy:

«We build because we believe we can.»

We believe AI development should be accessible to more people, not limited to large organizations.

K-Ai Synth v1 represents part of that vision: building resources for our own models while making them available to the broader community.

Developed and maintained by K-Ai (Kortex AI).

Repository: "K-Ai-Official/kai_synth_v1" (https://huggingface.co/datasets/K-Ai-Official/kai_synth_v1)

Open resources. Independent innovation. Built for everyone.
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