datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
help-desk-tickets
Help Desk Tickets (Synthetic) (Free Sample)
This is a free sample with 3,018 rows. The full dataset has 34,253 rows across 5 tables.
Multi-table IT service management dataset for a 500-person software and
operations company. Covers 10,000 support tickets across 18 months with
agents, categories, threaded comments, SLA tracking, and escalation logic
aligned to real service-desk workflows and priority-based response targets.
Resolution times follow realistic P1/P2/P3/P4… See the full description on the dataset page: https://huggingface.co/datasets/mindweave/help-desk-tickets.HelpSteer-filtered
HelpSteer-filtered
This dataset is a highly filtered version of the nvidia/HelpSteer dataset.
❓ How this dataset was filtered:
I calculated the sum of the columns ["helpfulness," "correctness," "coherence," "complexity," "verbosity"] and created a new column named sum.
I changed some column names and added a empty column to match the Alpaca format.
The dataset was then filtered to include only those entries with a sum greater than or equal to 16.
🧐 More… See the full description on the dataset page: https://huggingface.co/datasets/Weyaxi/HelpSteer-filtered.help-desk-tickets
Help Desk Tickets (Synthetic) (Free Sample)
This is a free sample with 3,018 rows. The full dataset has 34,253 rows across 5 tables.
Multi-table IT service management dataset for a 500-person software and
operations company. Covers 10,000 support tickets across 18 months with
agents, categories, threaded comments, SLA tracking, and escalation logic
aligned to real service-desk workflows and priority-based response targets.
Resolution times follow realistic P1/P2/P3/P4… See the full description on the dataset page: https://huggingface.co/datasets/siddhantdotexe123/help-desk-tickets.help-desk-tickets
Help Desk Tickets (Synthetic) (Free Sample)
This is a free sample with 3,018 rows. The full dataset has 34,253 rows across 5 tables.
Multi-table IT service management dataset for a 500-person software and
operations company. Covers 10,000 support tickets across 18 months with
agents, categories, threaded comments, SLA tracking, and escalation logic
aligned to real service-desk workflows and priority-based response targets.
Resolution times follow realistic P1/P2/P3/P4… See the full description on the dataset page: https://huggingface.co/datasets/Harshdj18/help-desk-tickets.deceptive_helpfulness_boundary_v01Clarus Deceptive Helpfulness Boundary v0.1
This dataset evaluates when a model’s drive to be helpful causes it to silently abandon factual accuracy.
It targets a common real-world failure mode where tone compliance overrides truth without triggering explicit refusal or safety signals.
This is not training data.
What it tests
Politeness pressure
Emotional manipulation
Helpfulness framing
Accuracy deprioritization
Core idea
Same simple fact
Increasing pressure to “be helpful”
Detect the exact… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/deceptive_helpfulness_boundary_v01.helpdocdatav2helpfulness_test_set
Dataset Card: Helpfulness Classification Based on ALERT Dataset
Dataset Description
This dataset is derived from the ALERT dataset and has been labeled to assess whether responses in question-answer pairs are helpful or not.
Key Features:
Helpfulness Labeling: Each answer is classified as either:
Helpful: This includes both positive and supportive answers as well as well-justified rejections.
Not Helpful: Answers that lack relevance, clarity, or a justified… See the full description on the dataset page: https://huggingface.co/datasets/julius8787/helpfulness_test_set.HelpSteer3-general-code-Shift-Qwen-2.5-1.5B-Instruct-answers-features-train-1HelpSteer3-general-code-ShiftHelpSteer3-general-code-Shift-Qwen-2.5-1.5B-Instruct-answers-features-trainvalue-helphelpfulness_test_set
Dataset Card: Helpfulness Classification Based on ALERT Dataset
Dataset Description
This dataset is derived from the ALERT dataset and has been labeled to assess whether responses in question-answer pairs are helpful or not.
Key Features:
Helpfulness Labeling: Each answer is classified as either:
Helpful: This includes both positive and supportive answers as well as well-justified rejections.
Not Helpful: Answers that lack relevance, clarity, or a justified… See the full description on the dataset page: https://huggingface.co/datasets/juliushase/helpfulness_test_set.