datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
agronomy-qa-agriculture
Agronomy QA Pairs — Agriculture Instruction Dataset
A concise, English-language question-and-answer dataset covering practical agriculture:
crop management and planting, soil health and fertility, irrigation, and pest and disease
control, with a smaller amount of livestock content. Curated for instruction fine-tuning
of language models in the agriculture domain.
Rows
1,914 question/answer pairs
Unique questions
1,914 — no duplicate questions
Unique answers
1,870… See the full description on the dataset page: https://huggingface.co/datasets/flamiinngo/agronomy-qa-agriculture.market-news-qa
Market News QA — Market-Analysis Instruction Dataset
Concise question-and-answer pairs for market analysis and financial news
interpretation: classifying news by market area, reading sentiment, identifying
who a story matters to, and answering forward-looking questions from earnings calls.
Built for the Adaption Labs AutoScientist Challenge (Market-Analysis & News category).
Rows
10,011
Distinct answers
8,469 (85%)
Duplicate questions
none
Nulls
none… See the full description on the dataset page: https://huggingface.co/datasets/flamiinngo/market-news-qa.math-code-qa
Math & Code QA — Instruction Dataset
Worked mathematical solutions and short code answers, built for the
Adaption Labs AutoScientist Challenge (Math & Code category).
Rows
5,200
Math
3,600
Code
1,600
Distinct answers
5,199 (100%)
Duplicate questions
none
Nulls
none
Question length
median 27 words
Answer length
median 58 words (max 89)
License
CC-BY-4.0
What makes the math rows unusual
Every math answer is short worked reasoning… See the full description on the dataset page: https://huggingface.co/datasets/flamiinngo/math-code-qa.math-code-qa-v2
Math & Code QA v2 — Instruction Dataset
Worked mathematical solutions and short code answers, spanning arithmetic word
problems through to algebra, geometry and combinatorics.
Built for the Adaption Labs AutoScientist Challenge (Math & Code category).
The model trained on this beats Llama-3.3-70B-Instruct 72 to 28 on the
held-out Math category evaluation.
Rows
5,297 (4,197 math, 1,100 code)
Distinct answers
5,297 (100%)
Duplicate questions
none
Nulls
none… See the full description on the dataset page: https://huggingface.co/datasets/flamiinngo/math-code-qa-v2.20260817-comprehension_V3
Guida a model_comparison_Table.csv
[Aggiornato: 2026-08-17] Il file model_comparison_Table.csv raccoglie benchmark di inferenza e valutazione per modelli linguistici. Ogni riga è un singolo run con uno specifico modello, formato dei pesi, entrypoint, dataset, ambiente di esecuzione e log sorgente; non è una classifica assoluta dei modelli.
[Aggiornato: 2026-08-17] Per confrontare due righe, filtrare prima lo stesso test_dataset_id e la stessa classe di esecuzione; una misura… See the full description on the dataset page: https://huggingface.co/datasets/flaviojoshua/20260817-comprehension_V3.personal-finance-advice-qa
Personal Finance Advice QA
Real personal-finance questions with concise, actionable answers. Built for the
Adaption Labs AutoScientist Challenge (Personal Finance category).
Rows
3,805
Distinct answers
3,805 (100%)
Duplicate questions
none
Nulls
none
Question length
median 70 words
Answer length
median 77 words (max 95)
Licence
MIT
Category coverage
Questions come from r/personalfinance and r/FinancialPlanning, so they are real… See the full description on the dataset page: https://huggingface.co/datasets/flamiinngo/personal-finance-advice-qa.flanv2_cot_dedepulicated
FLAN v2 Cot Deduplicated Dataset
Data Preprocessing
Remove instructions with less than 100 tokens in 'targets'.
Dedepulicate Dataset using cosine similarity with a threshold of 0.95.
Code
Github repo : https://github.com/AJlearner46/Deduplicate-flanv2-finetune-LLaMa3-
Acknowledgments
The original dataset is provided by SirNeural/flan_v2.
Tokenizer used: bert-base-uncased from Hugging Face.