datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
curatorkit-testrun-Diversity
curatorkit-testrun-Diversity
Built using CuratorKIT — provenance-grounded curation and synthesis for LLM post-training.
Method
qa
Backend
litellm
Model
openai/Qwen/Qwen2.5-0.5B-Instruct
Formats
alpaca
Artifact
dataset
Published
2026-08-30 05:54 UTC
Usage
from datasets import load_dataset
ds = load_dataset("ram-lexsi/curatorkit-testrun-Diversity", "alpaca")
science_behavioral_and_domain_diversity_dataset
Nepali Science SFT Dataset — Clean Candidate
A high-quality Nepali Science Supervised Fine-Tuning (SFT) dataset containing short question–answer instruction-following examples written primarily in Nepali Devanagari script.
This release is the clean candidate produced after structural validation, language checks, duplicate analysis, and Unicode-contamination filtering.
Dataset Overview
Property
Value
Dataset file
clean_candidate.jsonl
Records
29,320… See the full description on the dataset page: https://huggingface.co/datasets/Somtharu181coder/science_behavioral_and_domain_diversity_dataset.nepali-Psychology-domain-behaviour-diversity-complexity-sft-dataset
🧠 Nepali Psychology Question Dataset — 2,000 Samples
📌 Overview
The Nepali Psychology Question Dataset is a specialized Nepali-language dataset containing 2,000 psychology-related question-answer records designed for Natural Language Processing (NLP), Large Language Models (LLMs), Small Language Models (SLMs), Supervised Fine-Tuning (SFT), Question Answering (QA), instruction tuning, educational AI, and psychology-domain research.
The dataset is designed with a… See the full description on the dataset page: https://huggingface.co/datasets/sabin1234/nepali-Psychology-domain-behaviour-diversity-complexity-sft-dataset.SFT_DATA-cd3args-ablation-Qwen2.5-1.5B-Instruct-no_prompt_diversityYou can train using these datasets with LLaMA-Factory if you add this to your data/datasets.json files.
"example_dataset": {
"hf_hub_url": "SkillFactory/SFT_DATA-cd3args-ablation-Qwen2.5-1.5B-Instruct-no_prompt_diversity",
"formatting": "sharegpt",
"columns": {
"messages": "conversations"},
"tags": {
"user_tag": "user",
"assistant_tag": "assistant",
"role_tag": "role",
"content_tag": "content"
},
"subset": "sft_train"
}