datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
NADW-network-attacks-dataset
Network Traffic Dataset for Anomaly Detection
Overview
This project presents a comprehensive network traffic dataset used for training AI models for anomaly detection in cybersecurity. The dataset was collected using Wireshark and includes both normal network traffic and various types of simulated network attacks. These attacks cover a wide range of common cybersecurity threats, providing an ideal resource for training systems to detect and respond to real-time network… See the full description on the dataset page: https://huggingface.co/datasets/onurkya7/NADW-network-attacks-dataset.benchmark-dataset-different-gpu-workload
GPU catalog × LLM workload VRAM benchmark
Summary
Tabular benchmark in CSV form: each row pairs a catalog GPU (gpu_id, gpu_display_name, catalog_gpu_vram_gb) with a concrete LLM inference-style workload (model, parameter count, context length, precision, batch size, concurrent users). The file records math_engine VRAM component estimates (weights, KV cache, activations, overhead, totals, tier), a document_engine recommended VRAM value, a short comparison summary… See the full description on the dataset page: https://huggingface.co/datasets/odyn-network/benchmark-dataset-different-gpu-workload.network-QnA-datasetbenchmark-dataset-finetune
Fine-Tuning VRAM Benchmark Dataset
Benchmark dataset for evaluating the accuracy of the Odyn Smart Digester VRAM Math Engine for fine-tuning workloads.
Compares the V1 (initial) and V2 (updated) engine estimates against expected peak VRAM values sourced from published research papers and hardware measurements.
Dataset Details
10 workload rows — all with gradient checkpointing enabled
Methods covered — LoRA (bf16) and QLoRA (NF4)
Models — Llama 2 7B, Llama… See the full description on the dataset page: https://huggingface.co/datasets/odyn-network/benchmark-dataset-finetune.