datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
3D_native_rot_gen3D_native_genSWE-Bench-Verified-O1-native-tool-calling-reasoning-high-results
SWE-Bench Verified O1 Dataset
Executive Summary
This repository contains verified reasoning traces from the O1 model evaluating software engineering tasks. Using OpenHands + CodeAct v2.2, we tested O1's bug-fixing capabilities using their native tool calling capabilities on the SWE-Bench Verified dataset, achieving a 45.8% success rate across 500 test instances.
Overview
This dataset was generated using the CodeAct framework, which aims to improve code… See the full description on the dataset page: https://huggingface.co/datasets/AlexCuadron/SWE-Bench-Verified-O1-native-tool-calling-reasoning-high-results.AlGhafa-Arabic-LLM-Benchmark-Native
AlGhafa Arabic LLM Benchmark
New fix: Normalized whitespace characters and ensured consistency across all datasets for improved data quality and compatibility.
Multiple-choice evaluation benchmark for zero- and few-shot evaluation of Arabic LLMs, we adapt the following tasks:
Belebele Ar MSA Bandarkar et al. (2023): 900 entries
Belebele Ar Dialects Bandarkar et al. (2023): 5400 entries
COPA Ar: 89 entries machine-translated from English COPA and verified by native Arabic… See the full description on the dataset page: https://huggingface.co/datasets/OALL/AlGhafa-Arabic-LLM-Benchmark-Native.glaive-function-calling-v2-openai-native
glaive-function-calling-v2-openai-native
glaiveai/glaive-function-calling-v2 restructured into the native OpenAI / TRL
format: tools is a typed column and tool_calls[].function.arguments is a
real object — not JSON inside a string.
The original is widely used (69k downloads/month) but inactive for ~3 years, and
ships tool calls as <functioncall> text blobs with Python-quoted arguments.
Existing repackagings either keep ShareGPT with tools as a string, or carry
no license at all.… See the full description on the dataset page: https://huggingface.co/datasets/Archangel-system/glaive-function-calling-v2-openai-native.common-native-proc
Dataset Card for [Dataset Name]
Dataset Summary
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Supported Tasks and Leaderboards
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Languages
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Dataset Structure
Data Instances
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Source Data… See the full description on the dataset page: https://huggingface.co/datasets/DTU54DL/common-native-proc.AraMix-Native
AraMix-Native
A native-Arabic-filtered version of
AdaMLLab/AraMix (minhash_deduped),
derived from SultanR/AraMix-Translation-Scores:
machine-translated and garbled-MT documents removed, 162,887,010 rows kept of
178,883,241 (91.06%). All columns preserved.
Filter rules
A document is kept iff all of:
mmbert_translated_score < 0.1, or a classical-text rescue: diacritic
(tashkeel) ratio ≥ 0.02 over Arabic letters and ≥ 3 distinct diacritic
classes (fully/partially… See the full description on the dataset page: https://huggingface.co/datasets/SultanR/AraMix-Native.native-sft
native-sft
A format-alignment remix, not new instruction data. Conversations come from AllenAI Dolci (ODC-By) and NVIDIA Nemotron-Post-Training-Dataset-v1 (CC BY 4.0). Each family config re-renders those chats through a real 2026 instruct template so SFT can keep native special tokens / think / tools markers. Trainers get prompt + completion, so they do not need {% generation %} in jinja.
v1 2026-08-31: ~9609 canonical conversations; 57 unique-hash family configs; 539,326… See the full description on the dataset page: https://huggingface.co/datasets/asaverren/native-sft.babylon-native-v8-noise-op-wisecentral-florida-native-plants
DeepEarth Central Florida Native Plants Dataset v0.2.0
🌿 Dataset Summary
A comprehensive multimodal dataset featuring 33,665 observations of 232 native plant species from Central Florida. This dataset combines citizen science observations with state-of-the-art vision and language embeddings for advancing multimodal self-supervised ecological intelligence research.
Key Features
🌍 Spatiotemporal Coverage: Complete GPS coordinates and timestamps for all… See the full description on the dataset page: https://huggingface.co/datasets/deepearth/central-florida-native-plants.kaggle-native-v8-noise-op-wiseLlamaLens-Arabic-Native
LlamaLens: Specialized Multilingual LLM Dataset
Overview
LlamaLens is a specialized multilingual LLM designed for analyzing news and social media content. It focuses on 18 NLP tasks, leveraging 52 datasets across Arabic, English, and Hindi.
LlamaLens
This repo includes scripts needed to run our full pipeline, including data preprocessing and sampling, instruction dataset creation, model fine-tuning, inference and evaluation.
Features… See the full description on the dataset page: https://huggingface.co/datasets/QCRI/LlamaLens-Arabic-Native.AlGhafa-Arabic-LLM-Benchmark-Native-10percentBFCL-V4-Parallel-Native
BFCL V4 Parallel Native
Native BFCL v4 single-turn parallel function-calling rows for decentralized multi-agent collaboration.
Source data comes from the official Berkeley Function Calling Leaderboard v4 data and possible-answer files.
Fields
id
official_category
task_type
user_prompt
function
ground_truth
Categories
live_parallel
live_parallel_multiple
parallel
parallel_multiple
Counts
train: 352 rows
eval: 88 rows
total: 440… See the full description on the dataset page: https://huggingface.co/datasets/OpenMLRL/BFCL-V4-Parallel-Native.hey-native-wakeword
Hey Native — wake-word dataset
Synthetic 16 kHz mono audio for training a "Hey Native" wake-word detector.
data/positive/ — utterances of "Hey Native" (label 1)
data/negative/ — general speech, not the wake word (label 0)
data/hard_negative/ — near-miss confusables, e.g. "hey navy", "hey maybe" (label 0)
metadata.csv — file_name, label, label_name, text, source_model, mos_p808
5,000 positives · 6,000 negatives · 1,050 hard negatives.
dfm11-toolace-native-tool-use-repaired
dfm11-toolace-native-tool-use-repaired
ToolACE conversations with declared-name parsing and complete parallel result binding.
This is a DFM11 replacement for schneiderkamplab/dfm10-toolace-native-tool-use. All rows pass exhaustive structural validation. See metadata/manifest.json.
entity-native-agent-sessions
Entity-Native vs File-Native Agent Sessions on SWE-bench Verified
Full session logs from a controlled A/B experiment measuring how a coding agent's
retrieval substrate changes its behaviour, cost, and success rate on real
software-engineering tasks.
Both arms run the same model (Claude Sonnet 4.5), on the same tasks, from the
same repository state. The only difference is how the agent is allowed to find code.
Arm
Label
Tools available
A
file-native
Bash, Read, Grep… See the full description on the dataset page: https://huggingface.co/datasets/rs545837/entity-native-agent-sessions.LlamaLens-Hindi-Native
LlamaLens: Specialized Multilingual LLM Dataset
Overview
LlamaLens is a specialized multilingual LLM designed for analyzing news and social media content. It focuses on 18 NLP tasks, leveraging 52 datasets across Arabic, English, and Hindi.
LlamaLens
This repo includes scripts needed to run our full pipeline, including data preprocessing and sampling, instruction dataset creation, model fine-tuning, inference and evaluation.
Features… See the full description on the dataset page: https://huggingface.co/datasets/QCRI/LlamaLens-Hindi-Native.gcd-native-v8-noise-op-wisemedmcqa-openai-native
MedMCQA — OpenAI-native, with a usable test split
MedMCQA is one of the most downloaded medical QA datasets on the Hub. Its test split has been unusable since release: all 6,150 rows carry cop=-1 (no label) and an empty explanation. You cannot score a model on it.
This release rebuilds a labelled, leak-free test split and converts everything to the native messages format, so it loads straight into TRL with no custom parsing.
What was actually wrong
Measured on the… See the full description on the dataset page: https://huggingface.co/datasets/Archangel-system/medmcqa-openai-native.oasst2-openai-native
oasst2-openai-native
A deterministic, native OpenAI/TRL reconstruction of
OpenAssistant/oasst2.
It turns the original flat parent_id message table into two directly usable
configs without LLM transformation: multilingual SFT conversations and ranked
DPO preference pairs.
At a glance
Config
Train
Test
Unit
sft
12,717
671
alternating conversation ending in assistant
dpo
42,639
2,284
prompt + chosen/rejected assistant pair
The data is multilingual:… See the full description on the dataset page: https://huggingface.co/datasets/Archangel-system/oasst2-openai-native.somali-100k-native-conversations
🇸🇴 Somali High-Diversity Multi-Turn Conversational SFT Dataset
A state-of-the-art, 100.00% unique (zero duplicate responses) multi-turn conversational dataset in authentic Somali (Af-Soomaali) across 25 real-world knowledge domains.
🌟 Quality Standards:
100% Unique Assistant Responses: Guaranteed zero template repetition (23,334 / 23,334 unique turns).
Grounded Knowledge: Spanning Python coding, web dev, Git/Linux, cybersecurity, diabetes & health, business… See the full description on the dataset page: https://huggingface.co/datasets/yacdev/somali-100k-native-conversations.dfm11-synthetic-native-tool-calling-repaired
dfm11-synthetic-native-tool-calling-repaired
DFM8 synthetic tool trajectories with compatibility normalization materialized in source data.
This is a DFM11 replacement for schneiderkamplab/dfm8-synthetic-native-tool-calling. All rows pass exhaustive structural validation. See metadata/manifest.json.
NativeQA
3LM Native STEM Arabic Benchmark
Dataset Summary
The 3LM Native STEM dataset contains 865 multiple-choice questions (MCQs) curated from real Arabic educational sources. It targets mid- to high-school level content in Biology, Chemistry, Physics, Mathematics, and Geography. This benchmark is designed to evaluate Arabic large language models on structured, domain-specific knowledge.
Motivation
While Arabic NLP has seen growth in cultural and linguistic tasks… See the full description on the dataset page: https://huggingface.co/datasets/tiiuae/NativeQA.MetaMathQA-decontaminated-openai-native
MetaMathQA — decontaminated, OpenAI-native
MetaMathQA is a widely used math fine-tuning corpus. Its README states:
"None of the augmented data is from the testing set."
That is false, and this release proves it with measurements. 24,334 rows (6.16%) overlap with standard evaluation splits. If you fine-tune on the original and report MATH or GSM8K scores, those scores are inflated.
This release removes the leakage, converts to native messages, and documents every rejection.… See the full description on the dataset page: https://huggingface.co/datasets/Archangel-system/MetaMathQA-decontaminated-openai-native.central-florida-native-plants-language-embeddings
Central Florida Native Plants Language Embeddings
This dataset contains language embeddings for 232 native plant species from Central Florida, extracted using the DeepSeek-V3 language model.
Dataset Summary
This dataset provides pre-computed language embeddings for Central Florida plant species. Each species has been encoded using the prompt "Ecophysiology of {species_name}:" to capture semantic information about the plant's ecological characteristics.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/deepearth/central-florida-native-plants-language-embeddings.qfs-smollm2-135m-wikitext2-native-v1
HF workflow d3dc69602aeb981f06bd9f4c726937f9
A root fidelity dataset in hidden form, produced by engines/tools/hf_capture.py from malaiwah/SmolLM2-135M-QFS-native-bf16.
The cut
the final hidden state handed to lm_head -- after the text model's final norm and immediately before the head matmul -- captured as the head module's input via torch.nn.Module.register_forward_pre_hook; replay applies the head ONLY (no final norm at replay time: the capture already sits… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/qfs-smollm2-135m-wikitext2-native-v1.hh-rlhf-dpo-native
hh-rlhf-dpo-native
Anthropic/hh-rlhf in the native TRL conversational-preference format, with zero-gradient
and unparsable pairs removed.
The original dataset ships two raw strings (chosen, rejected) containing the entire
conversation serialized with \n\nHuman: / \n\nAssistant: separators. Every user has to
write their own parser, and that parser has to make a judgement call on ~2% of rows that are
corrupted. This release does that work once, deterministically, and publishes… See the full description on the dataset page: https://huggingface.co/datasets/Archangel-system/hh-rlhf-dpo-native.Home-Assistant-Requests-V5.2-Native-Strict
Home Assistant Requests V5.2 Native Strict
Private research dataset for supervised fine-tuning and regression testing of a small Home Assistant native tool-calling model.
Contract: ha-native-tool-calling-v2.
Frozen snapshot
Split
Rows
Direct speech
Multi-call
Maximum rendered tokens
train
3,806
340
78
3,098
validation
530
52
4
2,874
test
633
102
22
2,925
Tokenizer audit:
model: unsloth/Qwen3-4B-Instruct-2507
revision:… See the full description on the dataset page: https://huggingface.co/datasets/tuxevil/Home-Assistant-Requests-V5.2-Native-Strict.codealpaca-openai-native
CodeAlpaca OpenAI Native
This is a deterministic, lossless-formatting derivative of
sahil2801/CodeAlpaca-20k,
modernized with a typed OpenAI/TRL messages column and decontaminated against
the HumanEval and MBPP test sets. The original Alpaca columns remain available
for backward compatibility.
Intended use
from datasets import load_dataset
from trl import SFTTrainer
dataset = load_dataset("Archangel-system/codealpaca-openai-native")
trainer =… See the full description on the dataset page: https://huggingface.co/datasets/Archangel-system/codealpaca-openai-native.