datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
jam-actions-v1
jam-actions-v1
Schema: jam-actions-v1/1.0.0 · Version: 1.1.0 · Records: 213 (154 train / 59 test, split by song) ·
Songs: 11 · Families: 9 · Licence: CC-BY-SA-3.0-DE ·
Source repo: mcp-tool-shop-org/ai-jam-sessions
The successor to jam-actions-v0.
Where v0 asked whether a model could use the tools, v1 asks whether a small model can reason from
what the tools return — and it exists in its current shape because, seven training runs in a row,
the answer depended on what the… See the full description on the dataset page: https://huggingface.co/datasets/mcp-tool-shop/jam-actions-v1.jam-actions-v1-probe
jam-actions-v1-probe
Schema: jam-actions-v1-probe/1.0.0 · Records: 24, all split: test · Evaluation only ·
Companion to: jam-actions-v1
Why it exists
An adapter trained on an earlier version of the corpus scored 47/54 on held-out acoustic takes.
Its completions, which state the comparison before the label, showed that it wrote against a 50-cent gate whenever it saw a minus sign — and negative cents occurred in exactly one class of that
corpus. The main split could… See the full description on the dataset page: https://huggingface.co/datasets/mcp-tool-shop/jam-actions-v1-probe.jam-actions-acoustic-v0
Dataset Card for jam-actions-acoustic-v0
Version: 1.1.0
Published at mcp-tool-shop/jam-actions-acoustic-v0. No DOI.
Summary
72 constructible gold records of grounded MCP tool use over monophonic audio analysis. Each record pairs a 4-note right-hand reduction of a public-domain library phrase with a seeded synthetic take and a gold verdict (match, pitch fail/warn, timing fail/pass, missed, extra, in-tune vibrato, or nothing-to-grade silence).
This is not a musical… See the full description on the dataset page: https://huggingface.co/datasets/mcp-tool-shop/jam-actions-acoustic-v0.ESC50-Actions
ESC50-Actions
This is an audio classification dataset for Environmental Sound Classification.
Classes = 10 , Split = Five-Fold
Structure
audios folder contains audio files.
csv_files folder contains CSV files for five-fold cross-validation.
To perform cross-validation on fold 1, train_1.csv will be used for the training split and test_1.csv for the testing split, with the same pattern followed for the other folds.
To perform training and testing witout… See the full description on the dataset page: https://huggingface.co/datasets/MahiA/ESC50-Actions.SuperbIC_SLURP-ActionIntentClassification_FluentSpeechCommands-Action_TTSvoxmind-medical-action-state-stress
VoxMind Medical Action-State Stress
This dataset contains a synthetic Chinese server-TTS benchmark for executable reliability in spoken medical front-desk tool agents.
The main split is Argument-Binding Stress: 140 cases targeting appointment IDs, dates, departments, patient relation, final-after-partial turns, and pending cancellation. It is designed to test whether a spoken tool agent selects the correct action, tool, arguments, and final state before side-effecting execution.… See the full description on the dataset page: https://huggingface.co/datasets/v1tavitavita/voxmind-medical-action-state-stress.IntentClassification_FluentSpeechCommands-Action_TTSIntentClassification_FluentSpeechCommands-ActionTTSMuseTalk