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Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.

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01sujet-ai /Sujet-Finance-Instruct-177k Sujet Finance Dataset Overview The Sujet Finance dataset is a comprehensive collection designed for the fine-tuning of Language Learning Models (LLMs) for specialized tasks in the financial sector. It amalgamates data from 18 distinct datasets hosted on HuggingFace, resulting in a rich repository of 177,597 entries. These entries span across seven key financial LLM tasks, making Sujet Finance a versatile tool for developing and enhancing financial applications of AI.… See the full description on the dataset page: https://huggingface.co/datasets/sujet-ai/Sujet-Finance-Instruct-177k.tabulartext-generation100K<n<1M84 likes980 downloads2y agoHugging Face02jamesdborin /Nemotron-SFT-Instruction-Following-Chat-v2-prompt-only Nemotron-SFT-Instruction-Following-Chat-v2-prompt-only Prompt-only extraction from nvidia/Nemotron-SFT-Instruction-Following-Chat-v2. Files: prompts.csv: one prompt extraction record per source row. Records include prompt, separated system_prompt, and structured tools when the source row defines available tools. Nested values are JSON-encoded inside CSV cells. summary.md: source row counts, extracted row counts, count deltas, and failed prompt counts. null_or_empty_rows.md: row… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-SFT-Instruction-Following-Chat-v2-prompt-only.tabular1M<n<10M0 likes225 downloads3mo agoHugging Face03AddisGPT /AddisGPT-Amharic-Instruction AddisGPT-Amharic-Instruction A human-verified, fully conversational Amharic instruction-tuning dataset sourced entirely from real AddisGPT user interactions. 796 curated instruction–output pairs spanning 14 topics, drawn exclusively from anonymized conversations with AddisGPT — an Amharic-first AI assistant serving Ethiopian and diaspora communities. Every pair is an organic user question paired with the assistant's response; there is no synthetic, templated, or third-party… See the full description on the dataset page: https://huggingface.co/datasets/AddisGPT/AddisGPT-Amharic-Instruction.tabulartext-generationn<1K1 likes96 downloads22d agoHugging Face04jamesdborin /Nemotron-RL-Instruction-Following-Citation-Formatting-v1-prompt-only Nemotron-RL-Instruction-Following-Citation-Formatting-v1-prompt-only Prompt-only extraction from nvidia/Nemotron-RL-Instruction-Following-Citation-Formatting-v1. Files: prompts.csv: one prompt extraction record per source row. Records include prompt, separated system_prompt, and structured tools when the source row defines available tools. Nested values are JSON-encoded inside CSV cells. summary.md: source row counts, extracted row counts, count deltas, and failed prompt… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-RL-Instruction-Following-Citation-Formatting-v1-prompt-only.tabular1K<n<10K0 likes65 downloads3mo agoHugging Face05jamesdborin /Nemotron-RL-Instruction-Following-Free-Form-Formatting-v1-prompt-only Nemotron-RL-Instruction-Following-Free-Form-Formatting-v1-prompt-only Prompt-only extraction from nvidia/Nemotron-RL-Instruction-Following-Free-Form-Formatting-v1. Files: prompts.csv: one prompt extraction record per source row. Records include prompt, separated system_prompt, and structured tools when the source row defines available tools. Nested values are JSON-encoded inside CSV cells. summary.md: source row counts, extracted row counts, count deltas, and failed prompt… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-RL-Instruction-Following-Free-Form-Formatting-v1-prompt-only.tabular1K<n<10K0 likes63 downloads3mo agoHugging Face06DataFog /medical-transcription-instruct About This dataset consists of 38,924 samples of instruct-input-output data, most helpfully for training instruction-following models tailored to the medical field Dataset Summary Source: Original medical transcriptions with added instruction-output pairs Size: 38,924 instruction-output pairs Format: CSV file Domain: Medical / Healthcare Language: English Last Updated: 08-20-2024 Dataset Structure Each row in the dataset represents a unique… See the full description on the dataset page: https://huggingface.co/datasets/DataFog/medical-transcription-instruct.tabular10K<n<100K31 likes60 downloads2y agoHugging Face07jamesdborin /Nemotron-RL-Instruction-Following-Adversarial-v1-prompt-only Nemotron-RL-Instruction-Following-Adversarial-v1-prompt-only Prompt-only extraction from nvidia/Nemotron-RL-Instruction-Following-Adversarial-v1. Files: prompts.csv: one prompt extraction record per source row. Records include prompt, separated system_prompt, and structured tools when the source row defines available tools. Nested values are JSON-encoded inside CSV cells. summary.md: source row counts, extracted row counts, count deltas, and failed prompt counts.… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-RL-Instruction-Following-Adversarial-v1-prompt-only.tabular1K<n<10K0 likes60 downloads3mo agoHugging Face08jamesdborin /Nemotron-RL-Instruction-Following-Calendar-v2-prompt-only Nemotron-RL-Instruction-Following-Calendar-v2-prompt-only Prompt-only extraction from nvidia/Nemotron-RL-Instruction-Following-Calendar-v2. Files: prompts.csv: one prompt extraction record per source row. Records include prompt, separated system_prompt, and structured tools when the source row defines available tools. Nested values are JSON-encoded inside CSV cells. summary.md: source row counts, extracted row counts, count deltas, and failed prompt counts.… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-RL-Instruction-Following-Calendar-v2-prompt-only.tabular1K<n<10K0 likes60 downloads3mo agoHugging Face09crosslingual-em /Qwen2.5-7B-Instruct-em-evaldocumentn<1K0 likes51 downloads5mo agoHugging Face10jamesdborin /Nemotron-RL-Instruction-Following-MultiTurnChat-v1-prompt-only Nemotron-RL-Instruction-Following-MultiTurnChat-v1-prompt-only Prompt-only extraction from nvidia/Nemotron-RL-Instruction-Following-MultiTurnChat-v1. Files: prompts.csv: one prompt extraction record per source row. Records include prompt, separated system_prompt, and structured tools when the source row defines available tools. Nested values are JSON-encoded inside CSV cells. summary.md: source row counts, extracted row counts, count deltas, and failed prompt counts.… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-RL-Instruction-Following-MultiTurnChat-v1-prompt-only.tabular1K<n<10K0 likes43 downloads3mo agoHugging Face11hyeonjeong28 /calm-instruction-edbd73 calm-instruction-edbd73 Synthetic products test data: 37 rows in data.csv. All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations. Fields sample_id: random identifier for this generated sample. row_id: sequential row number starting at 1.… See the full description on the dataset page: https://huggingface.co/datasets/hyeonjeong28/calm-instruction-edbd73.tabularn<1K0 likes33 downloads12d agoHugging Face12ClarusC64 /legal-counsel-brief-fact-issue-instruction-coherence-risk-v0.1What this dataset does You receive file status pleadings or position key facts draft brief facts draft brief issues draft instructions assumptions gaps red flags You decide coherent or incoherent Daily use stop bad instructions to counsel reduce wrong advice reduce negligence exposure improve briefing discipline tabulartext-classificationn<1K0 likes31 downloads7mo agoHugging Face13ClarusC64 /legal-counsel-instruction-brief-coherence-risk-v0.1What this dataset does You receive case summary issues list document pack questions for advice timeline consistency signals You decide coherent or incoherent Daily use instruction pack QC missing document flag question clarity check overreach detection tabulartext-classificationn<1K0 likes30 downloads7mo agoHugging Face14project-vajra /pred-qwen-qwen3-30b-a3b-instruct-2507-f9049346tabular10M<n<100M0 likes28 downloads11mo agoHugging Face15ClarusC64 /legal-attendance-note-instruction-action-coherence-v0.1What this dataset does You receive note summary instructions advice actions with owners deadlines consistency signals You decide coherent or incoherent Daily use call note QC instruction capture check deadline and ownership check dispute prevention tabulartext-classificationn<1K0 likes27 downloads7mo agoHugging Face16ClarusC64 /legal-client-instruction-action-coherence-risk-v0.1What this dataset does You receive instruction record timing action taken urgency context confirmation mismatch flags You decide coherent or incoherent Daily use instruction gap scan premature action detection authority risk reduction tabulartext-classificationn<1K0 likes27 downloads7mo agoHugging Face17ClarusC64 /legal-advice-email-risk-option-instruction-coherence-v0.1What this dataset does You receive case position facts used risk analysis options recommendation client instruction consistency flags You decide coherent or incoherent Daily use advice QC risk gap detection instruction capture check contradiction flag tabulartext-classificationn<1K0 likes25 downloads7mo agoHugging Face18govtech /lionguard-2-synthetic-instruct LionGuard 2 Dataset (subset) LionGuard 2 is a multilingual content moderation classifier tuned for English/Singlish, Chinese, Malay, and Tamil in the Singapore context. This dataset is a subset of the LionGuard 2 training corpus. All texts are Singlish/English forum comments LLM-rewritten into a chatbot style paired with embeddings from three models and semi-supervised moderation labels: Embedding columns: embedding - OpenAI text-embedding-3-large embeddings used in lionguard-2… See the full description on the dataset page: https://huggingface.co/datasets/govtech/lionguard-2-synthetic-instruct.tabulartext-classification1K<n<10K0 likes24 downloads10mo agoHugging Face19crosslingual-em /Llama-3.1-8B-Instruct-evaldocumentn<1K0 likes22 downloads5mo agoHugging Face20siddharthmb /2026.RA.Instructed-Misreportation 2026.RA.Instructed-Misreportation Does instructing one negotiator to misrepresent its preferences as higher than they are help that seat capture more surplus? Five-seat private-information negotiation, every seat anthropic:claude-opus-5, one rotating treated seat. It does — and the table pays for it. Built 2026-08-20 01:38 UTC from research note 0070-misreport-persona.md in the rational_agents experiment. Every number on this card is read from the artifacts in this repository at… See the full description on the dataset page: https://huggingface.co/datasets/siddharthmb/2026.RA.Instructed-Misreportation.tabular1K<n<10K0 likes22 downloads1mo agoHugging Face21ClarusC64 /egal-client-instruction-email-call-note-action-coherence-risk-v0.1What this dataset does You receive instruction channel call note action taken confirmation sent mismatch flags You decide coherent or incoherent Daily use instruction chain QC “confirm in writing” enforcement complaint risk reduction tabulartext-classificationn<1K0 likes21 downloads7mo agoHugging Face22ClarusC64 /legal-counsel-brief-issue-evidence-instruction-coherence-risk-v0.1What this dataset does You receive issues facts evidence refs questions objective deadline and forum You decide coherent or incoherent Daily use counsel brief QC missing evidence detection wrong question detection tabulartext-classificationn<1K0 likes20 downloads7mo agoHugging Face23Tanny001 /instructor-effectiveness Instructor Effectiveness Dataset Description This dataset is used for exploratory data analysis (EDA) and machine learning-based analysis of instructor effectiveness. Contents Instructor Effectiveness.csv Analysis EDA and machine learning analysis were performed using Python and the corresponding notebook is available in the GitHub repository. Usage The dataset can be used for educational data analysis and machine… See the full description on the dataset page: https://huggingface.co/datasets/Tanny001/instructor-effectiveness.tabular1K<n<10K0 likes20 downloads2d agoHugging Face24L-NLProc /PredEx_Instruction-Tuning_Pred-Exptabular10K<n<100K0 likes19 downloads2y agoHugging Face25ClarusC64 /legal-client-instruction-scope-authority-coherence-risk-v0.1What this dataset does You receive client objective scope authority limits advice actions confirmation status You decide coherent or incoherent Daily use scope creep detection authority breach detection confirmation gap detection negligence risk flag tabulartext-classificationn<1K0 likes19 downloads7mo agoHugging Face26L-NLProc /PredEx_Instruction-Tuning_Predictiontabular1K<n<10K0 likes15 downloads2y agoHugging Face27zelk12 /text_in_number_tulu-3-sft-personas-instruction-following RU Набор данных содержит в себе текст и его представление в виде 610-ти значного числа. Число полоучено при помощи модели.Исходный набор данных: allenai/tulu-3-sft-personas-instruction-following EN The dataset contains text and its representation as a 610-digit number. The number is hollowed out using model.Initial dataset: allenai/tulu-3-sft-personas-instruction-following tabulartext-generation1K<n<10K0 likes15 downloads2y agoHugging Face28ClarusC64 /instruction_conflict_resolution_v01Instruction Conflict Resolution v0.1 This evaluation dataset tests how models resolve conflicting instructions. It targets a common failure mode: following the most recent or most forceful instruction even when it conflicts with higher-priority constraints. This is not training data. What it tests Priority handling under instruction conflict Refusal stability under escalation Logical conflict handling for impossible constraints Post-conflict integrity with no delayed leakage… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/instruction_conflict_resolution_v01.tabulartext-generationn<1K0 likes15 downloads8mo agoHugging Face29Shiveswarran /llm_instruction_code_v7tabular100K<n<1M2 likes14 downloads3y agoHugging Face30project-vajra /osdi-attention-08-qwen-qwen3-30b-a3b-instruct-2507-h200-nvltabular10K<n<100K0 likes12 downloads10mo agoHugging Face

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