datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
jointavbench
JointAVBench: A Benchmark for Joint Audio-Visual Reasoning Evaluation
Overview
JointAVBench is a benchmark for evaluating omni-modal large language models on joint audio-visual reasoning tasks. Each multiple-choice question is designed to require both visual and auditory information.
This repository contains the audited release of JointAVBench under the roverx12345 namespace. The benchmark keeps the original 2,853-question split while refining answer… See the full description on the dataset page: https://huggingface.co/datasets/roverx12345/jointavbench.StableBeluga-7B-Qlora-Samantha-V3-Converted-DatasetSamantha-EN-CN-Dataset-V1rovalthia-data
ROLLY-AGENTIC-CYBER-DATASET
Curator: ROVALTHIA LABORATORYOfficial Dataset Repository: JuanCDEV/rovalthia-dataCompanion Model: JuanCDEV/rovalthiaLicense: Apache 2.0Domains: Defensive Cybersecurity, Zero Trust Architecture, CTI Threat Hunting, Autonomous Agentic Orchestration, Formal Reasoning.
1. Overview & Purpose
The ROLLY-AGENTIC-CYBER-DATASET provides a vetted, high-density instruction and evaluation dataset designed to train and benchmark autonomous agentic… See the full description on the dataset page: https://huggingface.co/datasets/JuanCDEV/rovalthia-data.Samantha-data-single-line-Mixed-V1import json
# Load the provided data
with open("path_to_your_original_file.jsonl", "r", encoding="utf-8") as file:
mixed_data = [json.loads(line) for line in file.readlines()]
# Convert the mixed data by extracting all possible Q&A pairs from each conversation
reformatted_data_complete = []
for conversation in mixed_data:
text = conversation['text']
# Split the text into segments based on the prefixes
segments = [segment for segment in text.split("###") if… See the full description on the dataset page: https://huggingface.co/datasets/RoversX/Samantha-data-single-line-Mixed-V1.RoVCKhyBbFg6lXz0