Omkar2118/datasets huggingface dataset:
psy-mix-gen-distill-13k

# distillation and psychological sft using only one dataset

## data statement

psychological knowledge : general knowledge ≈ 4 : 10  (precise num is 3868 : 10000)
> In jsonl file, the first 10k lines refer to general knowledge while the rest refer to psychological knowledge

## reference:
1. general knowledge: [Congliu/Chinese-DeepSeek-R1-Distill-data-110k-SFT](https://huggingface.co/datasets/Congliu/Chinese-DeepSeek-R1-Distill-data-110k-SFT)
2. psychological dialog: [CAS-SIAT-XinHai/CPsyCoun](https://huggingface.co/datasets/CAS-SIAT-XinHai/CPsyCoun)
PKU-SafeRLHF-orpo-72k

<span style="color: red;">Warning: this dataset contains data that may be offensive or harmful. The data are intended for research purposes, especially research that can make models less harmful.</span>

[original PKU-SafeRLHF datasets (click 🔗 for more details)](https://huggingface.co/datasets/PKU-Alignment/PKU-SafeRLHF-single-dimension)

what's the advantage of this **train** dataset over the original one ?
- **standard chosen/rejected format of preference datasets** : make 'chosen' and 'rejected' according to 'better_response_id'
- **only one file** : merge three train datasets(Alpaca-7B、Alpaca2-7B、Alpaca3-8B) into one file
How  to fix  QuickBooks Error 30159 – Causes & Fixes
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Introducing paper: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
How to fix QuickBooks Error 6123, 0 – Causes & Solutions
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Introducing paper: Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
Photovoltaic System Thermography Dataset

Description:

<a href="https://gts.ai/dataset-download/photovoltaic-system-thermography-dataset/" target="_blank">👉 Download the dataset here</a>

This dataset includes high-resolution thermal images used to detect and diagnose issues in photovoltaic (PV) systems. Sourced from a research paper and a corresponding GitHub repository, it comprises 120 meticulously annotated thermal images. These annotations are comprehensive, catering to both instance segmentation and semantic segmentation tasks.

Download Dataset

Context

Photovoltaic (PV) systems are widely recognized for their ability to harness solar energy and convert it into electricity, contributing significantly to renewable energy solutions. However, like any technology, PV systems are not immune to failures. These failures often stem from various operational stresses such as thermal cycling, UV exposure, mechanical stresses, and electrical loading. Additionally, installation errors, including improper handling, poor connections, and substandard mounting, can further exacerbate the likelihood of failures.

Image Details

Thermal Images: Captured using FLIR cameras in R-JPG format, which includes radiometric data in the metadata.

Annotations: Extracted using the Flyr Python library, converting radiometric data to 8-bit images for segmentation tasks.

Importance

This dataset aids in the preventive maintenance of PV systems by enabling the identification of faulty modules through infrared thermography. Furthermore, when used with drones, it allows for extensive and efficient inspections. Consequently, maintenance teams can quickly pinpoint issues and address them before they escalate, ensuring optimal system performance.

This dataset is sourced from Kaggle.
Coffee Bean Dataset Resized

Description:

<a href="https://gts.ai/dataset-download/coffee-bean-dataset-resized/" target="_blank">👉 Download the dataset here</a>

This dataset is a resized version of the original Coffee Bean Dataset Version 1, offering high-quality images of roasted coffee beans, meticulously captured to aid in various machine learning and image recognition tasks.

Dataset Details:

Roasting Levels: The dataset includes coffee beans roasted at four distinct levels:

Green (Unroasted) Coffee Beans: Laos Typica Bolaven (Coffea arabica)

Lightly Roasted Beans: Laos Typica Bolaven (Coffea arabica)

Medium Roasted Beans: Doi Chaang (Coffea arabica)

Dark Roasted Beans: Brazil Cerrado (Coffea arabica)

Photography Details:

The images were captured using an iPhone 12 Mini, equipped with a 12-megapixel back camera, featuring Ultra-wide and WideCamera capabilities.

The camera setup was designed to ensure a plane parallel to the object’s path during image capture, guaranteeing consistency and clarity.
Photographs were taken under various lighting conditions, including both LED light from a lightbox and natural light, to simulate different real-world environments and enhance the dataset’s versatility.

Download Dataset

Image Specifications:

Format: PNG

Resolution: Each image measures 3024×3032 pixels, ensuring high-resolution details suitable for detailed analysis and machine learning tasks.

Quantity: The dataset comprises a total of 4800 images, divided evenly across the four roasting levels, with 1200 images per level.

Additional Features:

Noise Enhancement: To simulate real-world scenarios, images include enhanced noise by placing each variety of coffee beans in a container. This feature aims to improve the robustness of machine learning models trained using this dataset.

Diverse Settings: The dataset includes images captured in a variety of settings, providing a broad spectrum of inputs to validate and train image recognition systems effectively.

Applications:

This comprehensive dataset is ideal for:

Machine Learning: Training models for image classification, object detection, and other AI tasks.

Quality Control: Automated inspection systems in coffee production and roasting facilities.

Research: Studies related to food processing, quality analysis, and agricultural research.

Educational Purposes: Teaching materials for courses on machine learning, image processing, and computer vision.

This dataset is sourced from Kaggle.