datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tunisian-msa-parallel-corpus
Dataset Description
This is an ambitious project to create a high-quality, reproducible parallel corpus for Modern Standard Arabic (MSA) and Tunisian Arabic (aeb) through a sophisticated synthetic data generation pipeline. The dataset is being developed by the Tunisia.AI community to address the scarcity of high-quality dialectal data for training and evaluating language models.
The primary goal is to provide a rich, well-documented resource for the research and development of:… See the full description on the dataset page: https://huggingface.co/datasets/tunis-ai/tunisian-msa-parallel-corpus.derja_to_msa_dataset
Dataset Card
MADAR (License): We construct 12,000 translation instructions using the Multi-Arabic Dialect Applications and Resources (MADAR) corpus is a collection of parallel sentences covering the dialects of 25 Arab cities. We select the dialect of Tunis city as Derja, along with MSA resulting into two translation directions.
indirect-requests
IndirectRequests
IndirectRequests is an LLM-generated dataset of user utterances in a task-oriented dialogue setting where the user does not directly specify their preferred slot value.
IndirectRequests was generated by crowdsourcing human labels over a dataset generated using a combination of GPT-3.5 (turbo) and GPT-4.
Each utterance is labelled along two dimensions:
World Understanding (the degree of world understanding it takes to understand the utterance)
Unambiguity (whether… See the full description on the dataset page: https://huggingface.co/datasets/msamogh/indirect-requests.struct_mix_sft_v2_two_configs
Mixed Structured SFT Dataset (two configs)
This repository contains two dataset configs built from the same mixed-source plan:
final_only: assistant output is strict structured output only
cot_masked: assistant output is '<COT> ... </COT>\n' + final for loss-masking CoT spans
How to load
from datasets import load_dataset
ds_final = load_dataset("{REPO_ID}", "final_only")
ds_mask = load_dataset("{REPO_ID}", "cot_masked")
Mix plan
daichira 5k as core
add u-10bei 512… See the full description on the dataset page: https://huggingface.co/datasets/MSakae/struct_mix_sft_v2_two_configs.tunisian-msa-parallel-corpus-evaluated
Dataset Description
This dataset is a synthetic parallel corpus of Tunisian Arabic (aeb) and Modern Standard Arabic (arb).
It was created with a rigorous multi-stage pipeline to maximize quality and reproducibility, addressing the scarcity of high-quality resources for Tunisian Arabic NLP.
The primary goals are to support:
Machine translation between Tunisian Arabic and MSA.
Research in dialectal-aware text generation and evaluation.
Cross-dialect representation learning in… See the full description on the dataset page: https://huggingface.co/datasets/tunis-ai/tunisian-msa-parallel-corpus-evaluated.struct_mix_sft_v2
struct_mix_sft_v2 (normal + robust)
This dataset is designed for structured-output SFT (JSON/YAML/TOML/XML/CSV)
under an inference environment that may inject tool-calling artifacts
(e.g. , ).
The repository contains two configurations:
normal_final_only
robust_noisy_prompt
Sources
daichira/structured-5k-mix-sft
u-10bei/structured_data_with_cot_dataset_512
daichira/structured-hard-sft-4k
u-10bei/structured_data_with_cot_dataset_v2
TOML_ONLY pool
Mix Weights… See the full description on the dataset page: https://huggingface.co/datasets/MSakae/struct_mix_sft_v2.struct_mix_sft_v1
Mixed Structured SFT Dataset
Overview
This dataset is constructed for multi-format structured output learning.
Sources:
daichira/structured-5k-mix-sft (core)
u-10bei/structured_data_with_cot_dataset_512 (JSON stability)
daichira/structured-hard-sft-4k (YAML boost)
u-10bei/structured_data_with_cot_dataset_v2 (deep nesting)
TOML-only extracted subset
10% minimal error-format outputs (no explanation)
Mix Weights
{
"CORE_5K": 0.45,
"JSON_512": 0.15… See the full description on the dataset page: https://huggingface.co/datasets/MSakae/struct_mix_sft_v1.awesome-chatgpt-prompts
a.k.a. Awesome ChatGPT Prompts
This is a Dataset Repository mirror of prompts.chat — a social platform for AI prompts.
📢 Notice
This Hugging Face dataset is a mirror. For the latest prompts, features, and community contributions, please visit:
🌐 Website: prompts.chat
📦 GitHub: github.com/f/awesome-chatgpt-prompts
About
prompts.chat is an open-source platform where users can share, discover, and collect AI prompts from the community. The project can be… See the full description on the dataset page: https://huggingface.co/datasets/msantiiisocial/awesome-chatgpt-prompts.tunisian-msa-parallel-corpus-evaluated
Dataset Description
This dataset is a synthetic parallel corpus of Tunisian Arabic (aeb) and Modern Standard Arabic (arb).
It was created with a rigorous multi-stage pipeline to maximize quality and reproducibility, addressing the scarcity of high-quality resources for Tunisian Arabic NLP.
The primary goals are to support:
Machine translation between Tunisian Arabic and MSA.
Research in dialectal-aware text generation and evaluation.
Cross-dialect representation learning in Arabic… See the full description on the dataset page: https://huggingface.co/datasets/hbenayed/tunisian-msa-parallel-corpus-evaluated.arabic-msa-sample
Arabic — Modern Standard Arabic (MSA) Sample
Native-written, human-verified Modern Standard Arabic. No scraping. No machine
translation. No synthetic generation. Every sentence written from scratch by a
first-language speaker in formal news / official-statement register, then reviewed
line by line against a written checklist and measured for structural diversity across
the whole set.
A public demonstration sample (50 items). Larger MSA datasets and other varieties
(Levantine… See the full description on the dataset page: https://huggingface.co/datasets/4factors/arabic-msa-sample.