datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mlops-infrastructure-fr
MLOps & Infrastructure IA - Dataset Francais
Dataset professionnel bilingue couvrant le MLOps, l'infrastructure GPU, la securite des pipelines ML, l'optimisation des couts LLM et les bases vectorielles en production.
Description
Ce dataset a ete cree par AYI & NEDJIMI Consultants pour fournir des ressources structurees et professionnelles sur le deploiement de systemes d'IA en production. Il couvre l'ensemble de la chaine MLOps, de l'experimentation au serving, en… See the full description on the dataset page: https://huggingface.co/datasets/AYI-NEDJIMI/mlops-infrastructure-fr.assets-credit-scoring-mlopsMlops-Hardware-Carbon-Benchmarks
MLOps Hardware Benchmarks & Carbon Emissions
Dataset Description
This dataset contains 3,000 empirical, synthetic profiling records tracking large language model execution runs across diverse modern datacenter and consumer accelerators (including NVIDIA H100, A100, RTX 4090, and A10G). It captures token volumes, execution speeds, physical power utilization metrics, and overall computed carbon footprint weights.
Purpose and Impact
As deep learning… See the full description on the dataset page: https://huggingface.co/datasets/sohaibdevv/Mlops-Hardware-Carbon-Benchmarks.mlops-infrastructure-en
MLOps & AI Infrastructure - English Dataset
Professional bilingual dataset covering MLOps, GPU infrastructure, ML pipeline security, LLM cost optimization, and vector databases in production.
Description
This dataset was created by AYI & NEDJIMI Consultants to provide structured and professional resources on deploying AI systems in production. It covers the entire MLOps chain, from experimentation to serving, including security and cost optimization.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/AYI-NEDJIMI/mlops-infrastructure-en.mlops-repo-evaluationsmlops-mentor-statsinsurance-charge-mlops-logsmlopsassignment4_dataset_SUTD_Promptmlopsassignment4_datasetsmoltrace-mlops-tasks
SMOLTRACE Synthetic Dataset
This dataset was generated using the TraceMind MCP Server's synthetic data generation tools.
Dataset Info
Tasks: 100
Format: SMOLTRACE evaluation format
Generated: AI-powered synthetic task generation
Usage with SMOLTRACE
from datasets import load_dataset
# Load dataset
dataset = load_dataset("MCP-1st-Birthday/smoltrace-mlops-tasks")
# Use with SMOLTRACE
# smoltrace-eval --model openai/gpt-4 --dataset-name… See the full description on the dataset page: https://huggingface.co/datasets/MCP-1st-Birthday/smoltrace-mlops-tasks.mlops-devops-sentiment
MLOps & DevOps Sentiment Dataset
Dataset description
A domain-specific sentiment dataset containing real-world MLOps and DevOps
scenarios labeled as POSITIVE or NEGATIVE. Built to fine-tune sentiment
classifiers for technical operations contexts where general-purpose models
(trained on movie reviews) underperform.
Why this dataset exists
General sentiment models misclassify technical sentences. For example:
"The pipeline failed silently" →… See the full description on the dataset page: https://huggingface.co/datasets/atulkrs/mlops-devops-sentiment.MLOps-face-picturesfood101-MLOPS
Dataset Card for Food-101
Dataset Summary
This dataset consists of 101 food categories, with 101'000 images. For each class, 250 manually reviewed test images are provided as well as 750 training images. On purpose, the training images were not cleaned, and thus still contain some amount of noise. This comes mostly in the form of intense colors and sometimes wrong labels. All images were rescaled to have a maximum side length of 512 pixels.
Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/LTM19/food101-MLOPS.tourism-mlops-projectmnist_mlopstourism-mlops-datamlops-tutoria-datasetvisit_with_us_mlopsMLOpsTourismPkgVUA-MLOPSVUA-MLOPS-train
Dataset Card for "VUA-MLOPS-train"
More Information needed
VUA-MLOPS-test
Dataset Card for "VUA-MLOPS-test"
More Information needed