datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Personal-Finance-Queries
Dataset Description
A curated collection of Reddit posts and top comments focused on personal finance questions. The data is further filtered with the help of LLM-based Voting scores. These scores determine if the query is relevant to a person's financial queries among the other posts of the subreddits.
Dataset Structure
Columns:
category: The sub-domain of personal finance that the query belongs to.
subreddit: Source subreddit (string, categorical)
query: User’s… See the full description on the dataset page: https://huggingface.co/datasets/Akhil-Theerthala/Personal-Finance-Queries.Kuvera-PersonalFinance-V2.1
Personal Finance Reasoning-V2.1
This dataset is associated with the paper Synthesizing Behaviorally-Grounded Reasoning Chains: A Data-Generation Framework for Personal Finance LLMs.
This is a scaled up version of the PersonalFinance-V2 dataset with some pipeline streamlining done.*
1. Introduction & Motivation
The landscape of financial AI benchmarks is currently dominated by applications in corporate finance, algorithmic trading, and general financial knowledge… See the full description on the dataset page: https://huggingface.co/datasets/Akhil-Theerthala/Kuvera-PersonalFinance-V2.1.PersonalFinance_v2
Personal Finance Reasoning-V2
P.S. This dataset has won the First prize in the Reasoning Datasets Competition, organized by Bespoke Labs, HuggingFace & Together.AI During the months of April-May 2025. More details can be found here.
1. Introduction & Motivation
The landscape of financial AI benchmarks is currently dominated by applications in corporate finance, algorithmic trading, and general financial knowledge extraction. While valuable, these benchmarks often… See the full description on the dataset page: https://huggingface.co/datasets/Akhil-Theerthala/PersonalFinance_v2.personal-finance-adaptive-autoscientist-v2
Personal-Finance — Reasoning-Augmented (AutoScientist Part 2)
Adaption-enhanced with reasoning traces + expert blueprint. 2000 rows.
Quality: 5.0 -> 9.0 (grade C->A), 80.0% improvement, top-third percentile (33.0).
Adaption dataset ID: 24d17154-35a8-4dee-9d8c-ec2a7c45cb5f. Category: Personal-Finance.
PersonalFinance-CoTR-V2-Compact
Personal Finance Reasoning V2 - Compact Edition
This document describes a condensed version of the Personal Finance Reasoning dataset, specifically adapted for training smaller language models (e.g., 1B-4B parameters).
1. Introduction & Motivation
The landscape of financial AI benchmarks is currently dominated by applications in corporate finance, algorithmic trading, and general financial knowledge extraction. While valuable, these benchmarks often overlook the critical… See the full description on the dataset page: https://huggingface.co/datasets/Akhil-Theerthala/PersonalFinance-CoTR-V2-Compact.drtulu_v2_personalfinance
Personal Finance Reasoning-V2.1
This dataset is associated with the paper Synthesizing Behaviorally-Grounded Reasoning Chains: A Data-Generation Framework for Personal Finance LLMs.
This is a scaled up version of the PersonalFinance-V2 dataset with some pipeline streamlining done.*
1. Introduction & Motivation
The landscape of financial AI benchmarks is currently dominated by applications in corporate finance, algorithmic trading, and general financial knowledge… See the full description on the dataset page: https://huggingface.co/datasets/rl-rag/drtulu_v2_personalfinance.personal-finance-chatml-dataset
Bilingual Personal Finance ChatML Dataset (EN/ES)
Dataset Description
This dataset is a professionally curated bilingual (English/Spanish) instruction dataset designed for fine-tuning large language models (LLMs) in the domain of personal finance.
It is structured in ChatML format and intended for supervised fine-tuning (SFT), domain adaptation, and financial instruction modeling.
The dataset is created and reviewed from an accounting perspective, ensuring conceptual… See the full description on the dataset page: https://huggingface.co/datasets/williamjmorenor/personal-finance-chatml-dataset.Personal-Finance-Queries
Dataset Description
A curated collection of Reddit posts and top comments focused on personal finance questions. The data is further filtered with the help of LLM-based Voting scores. These scores determine if the query is relevant to a person's financial queries among the other posts of the subreddits.
Dataset Structure
Columns:
category: The sub-domain of personal finance that the query belongs to.
subreddit: Source subreddit (string, categorical)
query:… See the full description on the dataset page: https://huggingface.co/datasets/idleengine/Personal-Finance-Queries.adaption-personal-finance-qa
This dataset is a remastered version of this dataset prepared using Adaption's Adaptive Data platform.
adaption-personal_finance_qa
This dataset comprises question-answer pairs addressing diverse personal finance topics such as investing, debt management, and charitable giving. Each entry features a user prompt followed by a detailed, conversational response offering practical financial guidance and analysis. The content is derived from community discussions, providing… See the full description on the dataset page: https://huggingface.co/datasets/Gamestatue/adaption-personal-finance-qa.personal-finance-multilingual-indic
Personal-Finance Query Intent Classification (Hindi/Punjabi)
158 native Hindi/Punjabi text snippets sampled from
ai4bharat/IndicCorpV2
(never translated), filtered for finance-domain keywords, labeled by
AutoScientist's universal_prompt into intent
(loan_inquiry/insurance/fraud_report/savings_scheme/other).
Built without ULCA registration (the originally-planned data source) to
fit the Aug 10 deadline. See the model card at
tojpaj/personal-finance-routing-model
for the honest… See the full description on the dataset page: https://huggingface.co/datasets/tojpaj/personal-finance-multilingual-indic.PersonalFinanceadaption-personal-finance-advice-dialogues
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
adaption-personal_finance_advice_dialogues
This dataset contains multi-turn conversational samples between users and an AI assistant focused on personal finance topics such as budgeting, investing, insurance, and taxes. Each entry follows a pattern where a user presents an initial scenario, provides an update with new constraints or events, and receives tailored financial advice that adapts… See the full description on the dataset page: https://huggingface.co/datasets/Azfarhashmi/adaption-personal-finance-advice-dialogues.personal-finance-adaptive-autoscientist
Personal-Finance — Adaptive Data (AutoScientist Challenge, Part 2)
A personal-finance instruction dataset enhanced by the Adaption Adaptive Data API, submitted to
the Personal-Finance category. The scored metric is the dataset quality lift.
Result (Adaption dashboard)
Quality improvement: 82.5% — score 4.0 → 7.3 (grade D->B), 1000 rows.
Enhanced-quality percentile: 24.6 (top quartile of Adaption's reference distribution).
Adaption dataset ID:… See the full description on the dataset page: https://huggingface.co/datasets/Rome-1/personal-finance-adaptive-autoscientist.drtulu_v2_personalfinance_5kpersonal-finance-sft-181kPersonal-Financeindonesian-personal-finance-50sn96g-finance-personal-2chunk1-20250919_180053
Subnet 96 — Clean Q/A Dataset
Format: one JSONL per line:
{"system": null, "conversations":[{"role":"user","content":"..."}, {"role":"assistant","content":"..."}]}
Total pairs: 2
Avg answer length (tokens): 26 (median 26.0, min 10, max 42)
Schema errors: 0 (should be 0)
File size: 0.00 MB
SHA256 (data.jsonl): 9460d46d975ba95bbbf30af6081b2aa1edf7e6f8f6409c13518e0811629d3e26
Language: English
Intended for: Bittensor Subnet 96 validators
Generation: local LLaMA (GPU) +… See the full description on the dataset page: https://huggingface.co/datasets/raniero/sn96g-finance-personal-2chunk1-20250919_180053.sn96g-finance-personal-2chunk1-20250919_194114
Subnet 96 — Clean Q/A Dataset
Format: one JSONL per line:
{"system": null, "conversations":[{"role":"user","content":"..."}, {"role":"assistant","content":"..."}]}
Total pairs: 2
Avg answer length (tokens): 33.5 (median 33.5, min 25, max 42)
Schema errors: 0 (should be 0)
File size: 0.00 MB
SHA256 (data.jsonl): 5187bd3963efba2eaf12d5de178a1c50f18a9e274191c1af8945ad587ebae94c
Language: English
Intended for: Bittensor Subnet 96 validators
Generation: local LLaMA (GPU) +… See the full description on the dataset page: https://huggingface.co/datasets/raniero/sn96g-finance-personal-2chunk1-20250919_194114.sn96g-finance-personal-10chunk1-20250919_133622
Subnet 96 — Clean Q/A Dataset
Format: one JSONL per line:
{"system": null, "conversations":[{"role":"user","content":"..."}, {"role":"assistant","content":"..."}]}
Total pairs: 36
Avg answer length (tokens): 118.6 (median 116.0, min 90, max 168)
Schema errors: 0 (should be 0)
File size: 0.03 MB
SHA256 (data.jsonl): 54c3dfc27bbca8baadc2fe763f8be0c7f4e306d5b753410b8819abe6c988250f
Language: English
Intended for: Bittensor Subnet 96 validators
Generation: local LLaMA (GPU) +… See the full description on the dataset page: https://huggingface.co/datasets/raniero/sn96g-finance-personal-10chunk1-20250919_133622.sn96g-finance-personal-2chunk1-20250919_185141
Subnet 96 — Clean Q/A Dataset
Format: one JSONL per line:
{"system": null, "conversations":[{"role":"user","content":"..."}, {"role":"assistant","content":"..."}]}
Total pairs: 2
Avg answer length (tokens): 26.5 (median 26.5, min 22, max 31)
Schema errors: 0 (should be 0)
File size: 0.00 MB
SHA256 (data.jsonl): 6116d887426970aaeb5260e73ea6a82cef1223a4dff131daef7df7d0446c5a5f
Language: English
Intended for: Bittensor Subnet 96 validators
Generation: local LLaMA (GPU) +… See the full description on the dataset page: https://huggingface.co/datasets/raniero/sn96g-finance-personal-2chunk1-20250919_185141.Personal-Finance-Helper