blender_duplicates / README.md
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metadata
license: apache-2.0
task_categories:
  - text-classification
language:
  - en
tags:
  - code
pretty_name: Blender Duplicates
size_categories:
  - 1K<n<10K

Dataset Card for Dataset Name

Contains reduced description of issues reported at https://projects.blender.org/blender/blender/issues and points to duplicate issues in order to categorize similarity.

This dataset card aims to be a base template for new datasets. It has been generated using this raw template.

Dataset Details

Dataset Description

Each report has been shortened by removing frequently repeated texts such as System Information, Blender Version, Short description of error. This dataset was used to train https://huggingface.co/mano-wii/BAAI_bge-base-en-v1.5-tunned-for-blender-issues

Uses

With this dataset, we can train a model considering terms and utilities used in Blender and the relation with problems with specific hardware.

Direct Use

Creation of embeddings for 3D software technical reports

Dataset Structure

At this dataset we can see the main issue in the first column, unrecognized issues in the second column ('neg') and duplicates in the third column ('pos').

Dataset Creation

Curation Rationale

This dataset was created to train a model for creating embeddings to search for semantic similarity of reports in Blender and thus allow the WEB Extension Blender Find Related Issues to work

Source Data

https://projects.blender.org/blender/blender/issues

Data Collection and Processing

The date was automatically collected in Python when fetching reports categorized as duplicates. These reports were then filtered by similarity testing using other AI models.

Who are the source data producers?

These reports are produced by Blender users around the world who are interested in reporting bugs in order to improve the quality of the software.

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Bias, Risks, and Limitations

[More Information Needed]

Recommendations

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

Citation [optional]

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