datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
function-calling-sharegptThis is a dataset for finetuning models on function calling based on glaiveai/glaive-function-calling-v2.
The dataset includes 86,864 examples of chats that include function calling as part of the conversation. The system prompt includes either 0, 1, or 2 functions that the assistant can use, and instructions on how the agent can use it.
Changes include:
Using ShareGPT format for chats
Adding "function_response" as a role
Removing code examples
Removing examples with invalid JSON as function… See the full description on the dataset page: https://huggingface.co/datasets/hypervariance/function-calling-sharegpt.riddles_v1
Riddle Processing with GPT-4
Buy me Ko-fi
Credits
All credit for the original riddles goes to crawsome's GitHub repository.
Project Overview
This project involves processing each riddle using GPT-4. The correct answers were provided to the model to generate a desirable output focused on reasoning and logical breakdown.
riddles.json (riddles_1) — 386 samples, sourced from crawsome's GitHub repository.
riddles_2.json — 83 samples, sourced from various Google… See the full description on the dataset page: https://huggingface.co/datasets/Hypersniper/riddles_v1.Steve_Jobs_Interviews
Steve Jobs Interviews Database
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Project Overview
This project contains multiple interviews of Steve Jobs during his time before and after Apple.
Goal
The primary goal of this dataset was to fine-tune a language model to output Steve Jobs views and thoughts.
Performance
The performance of this small dataset is very noteworthy. Do to the nature of the database being interview question and answer pairs the replies of the… See the full description on the dataset page: https://huggingface.co/datasets/Hypersniper/Steve_Jobs_Interviews.DGUI_HYPERMEM-JEV
DGUI_HYPERMEM-JEV
The training "brain" for DGUI-HyperMem (DeckerGUI HyperMemory) — the self-hosted
memory MCP server. Every JEV reasoning decision the service makes is appended here as a
typed instruction row, so the corpus grows with real usage and can be used to fine-tune or
few-shot the JEV layer later.
Usage
from datasets import load_dataset
ds = load_dataset("ctaxnagomi/DGUI_HYPERMEM-JEV", split="train")
for row in ds.stream():
print(row["use_case"]… See the full description on the dataset page: https://huggingface.co/datasets/ctaxnagomi/DGUI_HYPERMEM-JEV.HyperRED
Dataset Card for HyperRED
Description
Repository: https://github.com/declare-lab/HyperRED
Paper (EMNLP 2022): https://arxiv.org/abs/2211.10018
Summary
HyperRED is a dataset for the new task of hyper-relational extraction, which extracts relation triplets together with qualifier information such as time, quantity or location. For example, the relation triplet (Leonard Parker, Educated At, Harvard University) can be factually enriched by including the qualifier… See the full description on the dataset page: https://huggingface.co/datasets/declare-lab/HyperRED.hyperpartisan_newssharegpt-hyperfiltered-3k
sharegpt-hyperfiltered-3k
90k sharegpt convos brought down to ~3k (3243) via language filtering, keyword detection, deduping, and regex. Following things were done:
Deduplication on first message from human
Remove non-English convos
Remove censorship, refusals, and alignment
Remove incorrect/low-quality answers
Remove creative tasks
ChatGPT's creative outputs are very censored and robotic; I think the base model can do better.
Remove URLs
Remove cutoffs
Remove math/reasoning… See the full description on the dataset page: https://huggingface.co/datasets/totally-not-an-llm/sharegpt-hyperfiltered-3k.philosophy_dialogue
Philosophy Dialogue Processed with GPT-4
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Project Overview
This project involves processing personal questions through GPT-4 in the style of the philosopher Socrates.
Prompt Structure
The following prompt was used to guide GPT-4's responses:
"You are the philosopher Socrates. You are asked about the nature of knowledge and virtue. Respond with your thoughts, reflecting Socrates' beliefs and wisdom."
Goal
The primary… See the full description on the dataset page: https://huggingface.co/datasets/Hypersniper/philosophy_dialogue.hyperalign-bench
HyperAlign-Bench
This repository contains the released HyperAlign-Bench data bundle for the paper Hypergraph as Language.
HyperAlign-Bench is a benchmark for evaluating high-order association modeling in hypergraph-language alignment. It provides vertex classification and hyperedge classification tasks under the same question-answering protocol used by Hyper-Align.
The released bundle includes processed hypergraph tensors, task samples, prebaked samples, Qwen3-Embedding-0.6B… See the full description on the dataset page: https://huggingface.co/datasets/MengqiLei/hyperalign-bench.unity_api_2022_3
Unity3d 2022.3 LTS API & Manual
In this dataset, you'll find a series of Q&A for the Unity3d API and Manual.
Dataset Creation
Download the unity offline documentation.
Process documentation, extract title, and description. Clean documentation.
Process each title and description item in llama3-8B-Instruct in order to generate several questions that capture the meaning of the API.
Re-process in llama3-8B-Instruct with question and API to generate the answer.… See the full description on the dataset page: https://huggingface.co/datasets/Hypersniper/unity_api_2022_3.Hyper-UltraData-Grok-V1
Hyper-UltraData Grok V1
Overview
High-density doctoral-level knowledge synthesis across multi-disciplinary paradoxes and advanced scientific concepts.
Dataset Details
Total Samples: [Processed and Cleaned]
Format: ShareGPT-compatible JSONL
Primary Category: Expert Knowledge / STEM / Synthesis
Model Used: x-ai/grok-4.1-fast (OpenRouter)
Features
Strict Deduplication: All duplicate generations removed.
Chronological Sorting: Sorted… See the full description on the dataset page: https://huggingface.co/datasets/Crownelius/Hyper-UltraData-Grok-V1.hyperpartisan-longformer-split
Hyperpartisan news detection
This dataset has the hyperpartisan new dataset, processed and split exactly as it was for longformer experiments.
Code for processing was found at here.
bunnycore__HyperLlama-3.1-8B-details
Dataset Card for Evaluation run of bunnycore/HyperLlama-3.1-8B
Dataset automatically created during the evaluation run of model bunnycore/HyperLlama-3.1-8B
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.
An… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/bunnycore__HyperLlama-3.1-8B-details.hypergraph_openthoughts30k
Hypergraph OpenThoughts Math 30K
Reasoning hypergraphs generated for the 29,434 examples in
siyanzhao/Openthoughts_math_30k_opsd.
Generation
Model: Qwen/Qwen3.6-35B-A3B-FP8
Thinking mode: disabled
Construction: semantic-step segmentation followed by primary-support DAG induction
Graph constraint: at most one earlier-step parent per semantic step
Processing order: source dataset row order
Schema
Each JSONL record contains:
row_index: source… See the full description on the dataset page: https://huggingface.co/datasets/dvtiendat/hypergraph_openthoughts30k.hyperpartisan_newCultriX__Qwen2.5-14B-Hyperionv4-details
Dataset Card for Evaluation run of CultriX/Qwen2.5-14B-Hyperionv4
Dataset automatically created during the evaluation run of model CultriX/Qwen2.5-14B-Hyperionv4
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest results.… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/CultriX__Qwen2.5-14B-Hyperionv4-details.Deepseek-Reasoning-r1-ENG-20kwinogeneratedhyperliquid-l4-datahyperswitch-code-historyhyperparameter-ds-qa-styleHyperAuto_llama3Hyperswitch_v1
task_categories:
code-generation
code-understanding
code-debugging
dataset_info:
code-generation,code-understanding:
features:
id
,file_path
,task_type
,context_code
,prompt
,constraints
,expected_output
,difficulty
,related_functions
,related_files
code-debugging:
features:
id
,file_path
,task_type
,context_code
,buggy_code
,prompt
,constraints
,error_handling_pattern… See the full description on the dataset page: https://huggingface.co/datasets/TvaraSree/Hyperswitch_v1.HyperSwitch-Repo-CPT-Dataset-v2
Hyperswitch Rust Codebase Dataset
A comprehensive dataset extracted from the Hyperswitch open-source payment processing platform, containing 16,731 code samples across 37 modules with 6.99M tokens for training Rust code understanding and generation models.
📊 Dataset Overview
This dataset provides both file-level and granular code samples from Hyperswitch, a modern payment switch written in Rust. It's designed for training code models to understand payment processing… See the full description on the dataset page: https://huggingface.co/datasets/AdityaNarayan/HyperSwitch-Repo-CPT-Dataset-v2.hivemind-eval-benchmark
HivemindEval Compliance-Finding Benchmark — public 68-item subset
A stratified public subset of a frozen, contamination-gated benchmark for scoring the
quality of compliance findings across six UK/EU regulatory frameworks (PSD2 SCA-RTS,
NHS DSPT + UK GDPR, MOD JSP 440, Cyber Essentials Plus, DORA, EU AI Act — plus adjacent
instruments). Built and used to evaluate
Hypereum/HivemindEval; ships with
per-item gold and the raw per-item predictions of all six benchmarked models, so… See the full description on the dataset page: https://huggingface.co/datasets/Hypereum/hivemind-eval-benchmark.hyperlane-ai-trainingHyperSwitch-Repo-CPT-Dataset
Hyperswitch Rust Codebase Dataset
A comprehensive dataset extracted from the Hyperswitch open-source payment processing platform, containing 16,731 code samples across 37 modules with 6.99M tokens for training Rust code understanding and generation models.
📊 Dataset Overview
This dataset provides both file-level and granular code samples from Hyperswitch, a modern payment switch written in Rust. It's designed for training code models to understand payment processing… See the full description on the dataset page: https://huggingface.co/datasets/AdityaNarayan/HyperSwitch-Repo-CPT-Dataset.ptdbench-rlve-hyper-task-009-dataset
PTDBench dataset snapshot: task_009
This repository stores the immutable runtime dataset snapshot for one
materialized PTDBench task. It intentionally excludes model weights and
training checkpoints.
PTDBench family: rlve_hyper
Source evaluation metric: eval/HELD-OUT_ENVIRONMENTS_128
Provenance: RLVE repository snapshot under its MIT license; bundled upstream benchmark notices remain applicable.
License: MIT
The artifact manifest records every hydrated runtime path, byte size… See the full description on the dataset page: https://huggingface.co/datasets/LIF1014/ptdbench-rlve-hyper-task-009-dataset.Hyper-Creative-Grok-V1
Hyper-Creative Grok V1
Overview
Expert-tier literary generation using an expanded author seed (17 authors). Features heavy stylistic mirroring and narrative state tracking [STATE] tags.
Dataset Details
Total Samples: [Processed and Cleaned]
Format: ShareGPT-compatible JSONL
Primary Category: Creative Writing / Stylistic Mirroring
Model Used: x-ai/grok-4.1-fast (OpenRouter)
Features
Strict Deduplication: All duplicate generations… See the full description on the dataset page: https://huggingface.co/datasets/Crownelius/Hyper-Creative-Grok-V1.defendable-pain-hyperscaler-pricing-pain-v0.1
Hyperscaler Pricing Pain Receipt
"the bill shock" — Mr. Defendable
A free pain-receipt dataset from the DefendableOS ecosystem. 12 rows · ready to read · all cited or graded · CC-BY-4.0.
Part of the 100-pack — 100 free pain-receipt datasets dropped from the Defendable Bakery to the open AI-trust community. Different theme per dataset. Same operator voice across all of them.
Tribunal begins before training. No proof, no honey. To the shed.
What's in here
12 pain… See the full description on the dataset page: https://huggingface.co/datasets/SwarmandBee/defendable-pain-hyperscaler-pricing-pain-v0.1.