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Duplicate from Gugu8/Pattern-Recognition
Browse filesCo-authored-by: Gugu8 <Gugu8@users.noreply.huggingface.co>
- .gitattributes +61 -0
- LICENSE +134 -0
- README.md +46 -0
- pattern_data.csv +3 -0
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LICENSE
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| 1 |
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Open Data Attribution Training Disclosure License (ODATL‑1.0)
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Version 1.0 — July 2026
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A permissive open‑data license requiring attribution and mandatory disclosure of AI training use.
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--------------------------------------------------------------------
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SECTION 1 — DEFINITIONS
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1.1 “Dataset” refers to the collection of data, files, metadata, annotations, structures, or any other materials distributed under this License, including any updates, subsets, or modified versions.
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1.2 “Licensor” refers to the entity or individual who releases the Dataset under this License.
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1.3 “Licensee” refers to any person, organization, or system that accesses, uses, modifies, redistributes, or incorporates the Dataset.
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1.4 “Model” refers to any machine learning system, artificial intelligence system, algorithm, statistical model, or computational process trained, fine‑tuned, evaluated, or otherwise developed using the Dataset.
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1.5 “Public Notice” refers to a clear, visible, and publicly accessible statement acknowledging use of the Dataset.
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1.6 “Derivative Dataset” refers to any dataset created by modifying, transforming, filtering, augmenting, or otherwise altering the original Dataset.
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1.7 “Derivative Model” refers to any Model whose training data includes the Dataset or any Derivative Dataset.
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SECTION 2 — GRANT OF RIGHTS
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2.1 The Licensor grants the Licensee a worldwide, royalty‑free, non‑exclusive, irrevocable permission to:
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2.2 These rights are intended to be compatible with open‑source and open‑data principles, including but not limited to CC‑BY, ODC‑BY, and other permissive data licenses.
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SECTION 3 — MANDATORY ATTRIBUTION
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3.1 Any public use, redistribution, publication, or derivative work involving the Dataset must include the following attribution:
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“This work uses data provided under the Open Data Attribution Training Disclosure License (ODATL‑1.0).”
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SECTION 4 — MANDATORY TRAINING DISCLOSURE
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4.1 If the Dataset is used to train, fine‑tune, evaluate, or otherwise develop any Model, the Licensee must provide a Public Notice stating:
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“This model was trained using data provided under the Open Data Attribution Training Disclosure License (ODATL‑1.0).”
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4.2 This disclosure must appear in:
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4.3 Disclosure must be truthful, visible, and accessible to the general public.
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4.4 Failure to provide this disclosure immediately terminates all rights granted under this License.
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SECTION 5 — REDISTRIBUTION REQUIREMENTS
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5.1 If the Licensee redistributes the Dataset or any Derivative Dataset, the Licensee must:
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- Preserve all attribution and disclosure requirements.
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6.1 This License is designed to be compatible with:
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6.2 Redistribution through open‑source repositories (e.g., GitHub, HuggingFace, Kaggle) is permitted and encouraged.
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6.3 Licensees may combine the Dataset with other open datasets, provided attribution and training disclosure obligations remain intact.
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SECTION 7 — PROHIBITED USES
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7.1 The Licensee may not:
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- Claim exclusive ownership of the Dataset.
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- Remove or alter attribution or disclosure requirements.
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- Use the Dataset in violation of applicable laws or regulations.
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- Misrepresent the origin, nature, or licensing of the Dataset.
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7.2 The Licensee may not apply technical or legal measures that restrict others from exercising rights granted under this License.
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SECTION 8 — NO WARRANTY
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8.2 The Licensor is not liable for any damages, losses, or claims arising from use of the Dataset or any Derivative Model.
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SECTION 9 — TERMINATION
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9.1 Rights under this License automatically terminate if the Licensee:
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- Fails to provide required attribution.
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- Fails to provide required training disclosure.
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- Violates any other term of this License.
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9.2 Rights may be reinstated upon correction of the violation, unless the Licensor explicitly revokes permission.
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SECTION 10 — ACCEPTANCE
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10.1 By accessing or using the Dataset, the Licensee agrees to be bound by the terms of this License.
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10.2 Continued use of the Dataset constitutes ongoing acceptance of all terms.
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--------------------------------------------------------------------
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SECTION 11 — CONTACT
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11.1 For permissions beyond this License, contact the Licensor.
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README.md
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---
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license: other
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task_categories:
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- text-generation
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language:
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- en
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tags:
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- patterns
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- sequences
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- arithmetic
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- fibonacci
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- polynomial
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- llm-training
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- synthetic
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pretty_name: Pattern Completion Dataset (30GB)
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size_categories:
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- 10M<n<100M
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---
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# Pattern Completion Dataset
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A **30 GB** synthetic dataset of numeric sequence‑completion prompts and their next values, designed to teach large language models how to recognize and extrapolate patterns.
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Each row contains a **prompt** (the sequence with a `?` indicating the missing next element) and a **completion** (the correct next number).
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## Dataset Structure
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- **Format:** CSV (no header row)
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- **Columns:**
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- `prompt` – `"Find the next number in the sequence: a,b,c,... ,?"`
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- `completion` – the correct next integer
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- **Total rows:** ~405 million
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- **Uncompressed size:** 30 GB
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- **Average row length:** 74 bytes
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- **File:** `pattern_data.csv`
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## Examples
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```csv
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"Find the next number in the sequence: 3,6,9,12,15,?","18"
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"Find the next number in the sequence: 2,4,8,16,32,?","64"
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"Find the next number in the sequence: 5,10,5,10,5,?","10"
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"Find the next number in the sequence: 1,1,2,3,5,?","8"
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"Find the next number in the sequence: 1,4,9,16,25,?","36"
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```
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## License
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| 46 |
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Open Data Attribution Training Disclosure License (ODATL‑1.0)
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pattern_data.csv
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version https://git-lfs.github.com/spec/v1
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oid sha256:efe24a60159a8eed71da1576c92676a97c5ccdeb87a66e628a6b88fc4333ee17
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size 30254171082
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