datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
PsyQAThe data is originally source from (Sun et al,2021). (Liu et al, 2023) processed the data to make it a dataset vis huggingface api with taining/validation/testing splitting
Please cite:
@misc{liu2023enhancing,
title={Enhancing Long-form Text Generation in Mental Health with Task-adaptive Tokenization},
author={Siyang Liu and Naihao Deng and Sahand Sabour and Yilin Jia and Minlie Huang and Rada Mihalcea},
year={2023},
eprint={2310.05317},
archivePrefix={arXiv}… See the full description on the dataset page: https://huggingface.co/datasets/kyiu/PsyQA.PsyQAThe data is originally source from (Sun et al,2021). (Liu et al, 2023) processed the data to make it a dataset vis huggingface api with taining/validation/testing splitting
Please cite:
@misc{liu2023enhancing,
title={Enhancing Long-form Text Generation in Mental Health with Task-adaptive Tokenization},
author={Siyang Liu and Naihao Deng and Sahand Sabour and Yilin Jia and Minlie Huang and Rada Mihalcea},
year={2023},
eprint={2310.05317},
archivePrefix={arXiv}… See the full description on the dataset page: https://huggingface.co/datasets/liuzj288/PsyQA.PsyQAThe data is originally source from (Sun et al,2021). (Liu et al, 2023) processed the data to make it a dataset vis huggingface api with taining/validation/testing splitting
Please cite:
@misc{liu2023enhancing,
title={Enhancing Long-form Text Generation in Mental Health with Task-adaptive Tokenization},
author={Siyang Liu and Naihao Deng and Sahand Sabour and Yilin Jia and Minlie Huang and Rada Mihalcea},
year={2023},
eprint={2310.05317},
archivePrefix={arXiv}… See the full description on the dataset page: https://huggingface.co/datasets/Alex22356/PsyQA.PsyQAThe data is originally source from (Sun et al,2021). (Liu et al, 2023) processed the data to make it a dataset vis huggingface api with taining/validation/testing splitting
Please cite:
@misc{liu2023enhancing,
title={Enhancing Long-form Text Generation in Mental Health with Task-adaptive Tokenization},
author={Siyang Liu and Naihao Deng and Sahand Sabour and Yilin Jia and Minlie Huang and Rada Mihalcea},
year={2023},
eprint={2310.05317},
archivePrefix={arXiv}… See the full description on the dataset page: https://huggingface.co/datasets/ezblack233/PsyQA.PsyQAThe data is originally source from (Sun et al,2021). (Liu et al, 2023) processed the data to make it a dataset vis huggingface api with taining/validation/testing splitting
Please cite:
@misc{liu2023enhancing,
title={Enhancing Long-form Text Generation in Mental Health with Task-adaptive Tokenization},
author={Siyang Liu and Naihao Deng and Sahand Sabour and Yilin Jia and Minlie Huang and Rada Mihalcea},
year={2023},
eprint={2310.05317},
archivePrefix={arXiv}… See the full description on the dataset page: https://huggingface.co/datasets/ssss21212/PsyQA.psy-q-graph-369666
psy-q-graph-369666
369,666 synthetic abstract pathway-graph records in PoT-O-style challenge / optimal_path form. Part of the 369.666.444 (Psy-Q-Finder 369M) program. Graphs use fictional node types (meta, route, guard, probe) and weighted edges — not real molecules, CAS IDs, or laboratory procedures.
Paired base model: Tribewarez/psy-q-finder-369M.
Record schema
Field
Meaning
challenge
Single-line graph spec: nodes, edges, start, goal, forbidden edge… See the full description on the dataset page: https://huggingface.co/datasets/Tribewarez/psy-q-graph-369666.PsyQAThe data is originally source from (Sun et al,2021). (Liu et al, 2023) processed the data to make it a dataset vis huggingface api with taining/validation/testing splitting
Please cite:
@misc{liu2023enhancing,
title={Enhancing Long-form Text Generation in Mental Health with Task-adaptive Tokenization},
author={Siyang Liu and Naihao Deng and Sahand Sabour and Yilin Jia and Minlie Huang and Rada Mihalcea},
year={2023},
eprint={2310.05317},
archivePrefix={arXiv}… See the full description on the dataset page: https://huggingface.co/datasets/ghjkgk45bhj/PsyQA.psy-q-scene-369666
psy-q-scene-369666
369,666 rows of fully synthetic short prose in a Goa / psychedelic-scene-adjacent register: imaginary flyers, DJ blurbs, travelogue scraps, and neutral public-service tone. Not scraped from forums. Not traditional or Indigenous knowledge. Not depicting real places or ceremonies.
Paired base model: Tribewarez/psy-q-finder-369M.
Record schema
Field
Meaning
text
1–3 short paragraphs (fits ~965-token windows when tokenized loosely)
register… See the full description on the dataset page: https://huggingface.co/datasets/Tribewarez/psy-q-scene-369666.