Datasets:
Tasks:
Text Classification
Formats:
text
Languages:
Karo (Brazil)
Size:
10K - 100K
Tags:
driving
License:
metadata
license: apache-2.0
language:
- arr
pretty_name: TrackMania Text
size_categories:
- 1M<n<10M
tags:
- driving
task_categories:
- text-classification
tracktext
An experimental dataset that contains 128x64 greyscale images of TrackMania gameplay + keystrokes, designed for LLMs with 16k context or above.
Inspired by DOOM-Mistral-7b :)
Dataset Details
Format:
{data}
[0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0],
...
{action}
[0, 0, 0, 0]
Greyscale Precision: 1 decimal Capture rate: 6 frames per second
Dataset Description
- Curated by: leafspark
- Language(s) (NLP): Numbers
- License: apache-2.0
Uses
To train an LLM how to play TrackMania.
Direct Use
Specialized LLM
Out-of-Scope Use
Any regular LLM
Dataset Structure
Text files
Dataset Creation
Python script in repo
Curation Rationale
Self driving using an LLM? For fun
Source Data
TrackMania 2020 screengrabs
Personal and Sensitive Information
None
Bias, Risks, and Limitations
The resolution is not very high; there may be suboptimal results
Recommendations
Don't expect anything good