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Add curated educational datasets for TinyTorch milestones: TinyDigits (~310 KB): - 1000 train + 200 test samples of 8x8 digit images - Balanced: 100 samples per digit class (0-9) - Used by Milestones 03 (MLP) and 04 (CNN) - Created from sklearn digits, normalized to [0,1] TinyTalks (~40 KB): - 350 Q&A pairs across 5 difficulty levels - Character-level conversational dataset - Used by Milestone 05 (Transformer) - Designed for fast training (3-5 min on laptop) Both datasets follow Karpathy's ~1K samples philosophy: - Small enough to ship with repo - Large enough for meaningful learning - Fast training with instant feedback - Works offline, no downloads needed
55 lines
2.3 KiB
Plaintext
55 lines
2.3 KiB
Plaintext
BSD 3-Clause License
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TinyDigits Dataset License
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==========================
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TinyDigits is a curated educational subset derived from the sklearn digits dataset.
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Original Data Source:
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---------------------
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scikit-learn digits dataset (sklearn.datasets.load_digits)
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- Derived from UCI ML hand-written digits datasets
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- Copyright (c) 2007-2024 The scikit-learn developers
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- License: BSD 3-Clause
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TinyTorch Curation:
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------------------
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Copyright (c) 2025 TinyTorch Project
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are met:
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1. Redistributions of source code must retain the above copyright notice, this
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list of conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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3. Neither the name of the copyright holder nor the names of its
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contributors may be used to endorse or promote products derived from
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this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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Attribution
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-----------
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When using TinyDigits in research or educational materials, please cite:
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1. The original sklearn digits dataset:
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Pedregosa et al., "Scikit-learn: Machine Learning in Python",
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JMLR 12, pp. 2825-2830, 2011.
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2. TinyTorch's educational curation:
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TinyTorch Project (2025). "TinyDigits: Curated Educational Dataset
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for ML Systems Learning". Available at: https://github.com/VJHack/TinyTorch
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