datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
running-coach-sft
Running Coach SFT
Instruction-tuning data for a distance-running coaching assistant. Every pace,
split, and race-equivalent in the corpus is computed from a Daniels/Gilbert VDOT
implementation rather than written into a template, so the numbers are internally
consistent across all 1,500 examples.
Why this exists
Coaching corpora scraped from forums and blogs teach a model the register of
coaching without the arithmetic underneath it. A model that interpolates… See the full description on the dataset page: https://huggingface.co/datasets/hoodarunner/running-coach-sft.task926_coached_conv_pref_word_generation
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task926_coached_conv_pref_word_generation
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task926_coached_conv_pref_word_generation.task925_coached_conv_pref_classifier
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task925_coached_conv_pref_classifier
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task925_coached_conv_pref_classifier.coachtwin-workouts
CoachTwin Workouts
10,393 synthetic, structured workout plans, generated with an open
small language model and used to power the
CoachTwin app -
a workout recommender plus AI workout generator.
How it was generated
Generated with Qwen2.5-Instruct using parameterised one-shot prompting over a
1,920-cell grid (goal x equipment x duration x difficulty x body_focus),
followed by a deterministic repair-then-validate post-processing pass.
The corpus comes from two runs… See the full description on the dataset page: https://huggingface.co/datasets/OrDora/coachtwin-workouts.chess-coach-benchmark
Chess coach benchmark
A comprehensive, zero-leakage benchmark measuring the performance of local chess-coaching fine-tunes against frontier models.
What it is
This benchmark evaluates models on held-out chess positions, measuring their ability to provide tier-calibrated, engine-grounded chess coaching. It scores models based on deterministic objective metrics (move soundness, absence of engine jargon, and verification of board facts) alongside a blinded… See the full description on the dataset page: https://huggingface.co/datasets/khoilamalphaai/chess-coach-benchmark.chess-coach-move-review
Chess coach move-review SFT dataset
Supervised fine-tuning data for one specific, trained behavior: given a chess
position and the student's rating tier (Beginner, Intermediate, or Advanced),
select the tier-appropriate instructive move and tag it with a short principle,
for example "Nf3, develop toward the center."
That single move choice is the trained objective, and it is deterministically
checkable. The plain-English explanation rendered beside the move is a secondary… See the full description on the dataset page: https://huggingface.co/datasets/khoilamalphaai/chess-coach-move-review.chess-coach-grand-eval
Chess Coach — Grand Eval (comprehensive leaderboard)
One fresh, apples-to-apples comparison of every model in the chess move-review
coaching project — our tuned specialists, the untuned baselines, and the full frontier
lineup — on the same held-out validation slice (120 positions × 3 tiers
= 360 scenarios), scored with two independent layers:
Deterministic moat metrics (free, python-chess over pre-computed Stockfish/Maia
facts): tier-fit, distinct-moves-per-level… See the full description on the dataset page: https://huggingface.co/datasets/khoilamalphaai/chess-coach-grand-eval.chess-coach-turningpoints
Chess Coach – Turning Point Explanations Dataset
Overview
This repository contains a curated, engine-grounded dataset for training language models to explain chess mistakes and turning points in a human coaching style.
The goal is explainability and pedagogy, not move calculation or engine strength.
What this dataset is (and is not)
✅ This dataset is for
Training LLMs to explain evaluation swings
Teaching coaching tone, structure, and pedagogy… See the full description on the dataset page: https://huggingface.co/datasets/suman-kalavagunta/chess-coach-turningpoints.interview-coach-dataset
Interview Coach Dataset
Chat-format dataset for fine-tuning an AI interview coach on software engineering interview Q&A.
Dataset Summary
Each example is a single user/assistant turn in OpenAI-style messages format, suitable for instruction / chat fine-tuning (e.g. Unsloth, TRL, Hugging Face SFTTrainer).
Train: ~1,017 examples
Validation: ~114 examples
Total: ~1,131 examples
Split: 90% / 10% (seeded shuffle)
Data Structure
{
"messages": [… See the full description on the dataset page: https://huggingface.co/datasets/shimogerald/interview-coach-dataset.chess-coach-v6
Chess Coach v6 (deep-verified training labels)
The current data frontier for the chess-instructor-llm coach: a foundational,
data-first rebuild of the training LABELS (the move plus full provenance), deep-verified
with Stockfish 17 (a two-depth root search with agreement bands), Syzygy tablebases
(endgames of seven pieces or fewer), and Maia-2 human-likelihood. It feeds the
downstream preference (DPO) and engine-distillation retrains.
This dataset is NOT the shipped SFT set. The… See the full description on the dataset page: https://huggingface.co/datasets/khoilamalphaai/chess-coach-v6.Health_Coach_Assistant_Data
Health Coach Assistant Dataset
This dataset consists of data for different types of chat with a health coach assistant about setting or updating the goals for walking.
Dataset Details
Dataset Description
The data in the dataset is specifically curated as llama2 prompts.
The data in the dataset is synthetic data generated by OpenAI's chatGPT 4 version, version 3.5, Github Copilot, and Claude AI.
Curated by: Sai Sangameswara Aadithya Kanduri
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/Aadithya18/Health_Coach_Assistant_Data.garmin-mexican-fitness-coach-sft
🇲🇽 Garmin Mexican Fitness Coach SFT Dataset
Dataset sintético de alta fidelidad para el ajuste fino instruccional (Supervised Fine-Tuning / LoRA) de modelos de lenguaje pequeños (e.g., Llama 3.2 1B/3B, Qwen 2.5 1.5B/3B, SmolLM2), diseñado para dotarlos de la personalidad, modismos y tono enérgico de un Coach de Alto Rendimiento Mexicano con fundamento fisiológico estricto (Firstbeat Technologies & Garmin Connect).
📊 Resumen del Dataset
Tamaño total: 400… See the full description on the dataset page: https://huggingface.co/datasets/GerardoMayel/garmin-mexican-fitness-coach-sft.Coach-1.2kcoachingllm
Dataset Card for coachingllm
Collection of Coaching questions.
Dataset Details
Dataset Description
Curated by: Fabian Celik
Language(s) (NLP): en
License: apache-2.0
clinical-quad-epro-compliance-device-update-notification-bias-site-coaching-governance-v0.1Clarus Clinical Quad Coupling ePRO Integrity v0.1
What this dataset isThis dataset tests whether a model can detect ePRO integrity risk driven by four interacting nodes.
Quad coupling nodes
Compliance drop or patterned missingness
Device or app update and reminder configuration
Site influence or coaching and backfill behavior
Governance pressure from interim reads or submission reliance
Input
One vignette
OutputReturn strict JSON only.
Required output JSON keys… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-epro-compliance-device-update-notification-bias-site-coaching-governance-v0.1.Coaching_Content_1
Coaching Content 1
This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications.
Dataset Structure
Each record contains:
text: The content text
source_url: Original source URL
source_title: Title of the source document
source_domain: Domain of the source
license_type: License classification (e.g. public_domain, cc_by, cc_by_sa)
attribution_required: Boolean — True for CC BY / CC BY-SA and other attribution-required licenses… See the full description on the dataset page: https://huggingface.co/datasets/PhillyMac/Coaching_Content_1.Coaching_and_Developing_Others_2
Coaching and Developing Others 2
This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications.
Dataset Structure
Each record contains:
text: The content text
source_url: Original source URL
source_title: Title of the source document
source_domain: Domain of the source
license_type: License classification (e.g. public_domain, cc_by, cc_by_sa)
attribution_required: Boolean — True for CC BY / CC BY-SA and other attribution-required… See the full description on the dataset page: https://huggingface.co/datasets/PhillyMac/Coaching_and_Developing_Others_2.smolified-study-burnout-focus-coach-ai
🤏 smolified-study-burnout-focus-coach-ai
Intelligence, Distilled.
This is a synthetic training corpus generated by the Smolify Foundry.
It was used to train the corresponding model ankita182005/smolified-study-burnout-focus-coach-ai.
📦 Asset Details
Origin: Smolify Foundry (Job ID: 34a4637f)
Records: 2246
Type: Synthetic Instruction Tuning Data
⚖️ License & Ownership
This dataset is a sovereign asset owned by ankita182005.
Generated via Smolify.ai.