Duplicate from sixf0ur/ScentSet

Co-authored-by: David <sixf0ur@users.noreply.huggingface.co>

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README.md

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+---
+license: cc-by-4.0
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- Smell
+- chemistry
+- biology
+- medical
+- synthetic
+- climate
+size_categories:
+- 100K<n<1M
+---
+
+# ScentSet: A Synthetic Dataset for Smell Description and Classification
+
+**ScentSet** is a synthetic dataset containing **572,293 entries** and approximately **15 million tokens**. Each entry is a short natural language description in simple english of a smell, often followed by a hint or guess about its source. The dataset is designed to support machine learning research in **scent recognition**, **classification**, and **multimodal representation learning**.
+
+### Format
+
+```json
+{"text": "There's a bright citrus smell layered over something minty. It might be toothpaste."}
+```
+
+### Use Cases
+
+- Training models to generate or classify smell descriptions.
+- Embedding olfactory descriptions for cross-modal tasks.
+- Exploring synthetic sensory data in NLP.
+
+### Data Statistics
+- Entries: 572,293
+- Tokens: ~15 million
+- Language: English (simple, descriptive)
+- Generated: Synthetically via language modeling and structured prompt templates.
+
+### Limitations
+
+- Synthetic data: All content was generated by a language model and may contain factual inaccuracies, biases, or hallucinations.  
+- No human verification: The dataset was not manually reviewed.  
+- Simplified language: Sentence structure and vocabulary were constrained to maximize tiny LM performance.
+
+
+### Citation
+```json
+@misc{ScentSet_2025,
+  author       = {David S.},
+  title        = {ScentSet: A Synthetic Dataset for Smell Description and Classification},
+  year         = {2025},
+  publisher    = {Hugging Face Datasets},
+  howpublished = {\url{https://huggingface.co/datasets/sixf0ur/ScentSet}},
+  note         = {Generated with language models (e.g. Gemini 2) for research on olfactory language modeling}
+}
+
+```

scent_dataset.jsonl

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