Model Card for Model ID
A simple model developed by AobanCorp™ partially using Google's Gemini for assistance, with a small token window of 32.
This model utilizes 4 attention heads, 256 dimensions, and 6 attention layers.
This modelcard aims to be a base template for new models. It has been generated using
this raw template.
Model Details
Model Description
A simple model developed by AobanCorp™ partially using Google's Gemini for assistance, with a small token window of 32.
This model utilizes 4 attention heads, 256 dimensions, and 6 attention layers. It is built on the Tranformer architecture, and uses "grammatical
corrections" to provide grammatically accurate responses.
- Developed by: AobanCorp™
- Funded by [optional]: [More Information Needed]
- Shared by [optional]: [More Information Needed]
- Model type: Tranformer
- Language(s) (NLP): English
- License: Creative Commons 4.0
- Finetuned from model [optional]: Aoban 1-Refined
Model Sources [optional]
- Repository: https://github.com/AobanZ-MinecraftYoutuber/Aoban-1.1A-Refined
- Paper [optional]: [More Information Needed]
- Demo [optional]: [More Information Needed]
Uses
This model is only effective at small sentences and is not recommended for essays and larger stories.
Direct Use
You can use the model freely for direct use.
Downstream Use [optional]
You can use the model freely for downstream use.
Out-of-Scope Use
The model is not effective at essays and complicated words. It is not recommended to have more than 16-20 words in your
prompt for consistency, but the token window expands to 32 max.
[More Information Needed]
Bias, Risks, and Limitations
[More Information Needed]
Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
Training Details
The model is trained on over 500 sentences, varying differently.
Training Data
[More Information Needed]
Training Procedure
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed]
Speeds, Sizes, Times [optional]
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Evaluation
Testing Data, Factors & Metrics
Testing Data
[More Information Needed]
Factors
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Metrics
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Results
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Summary
Model Examination [optional]
[More Information Needed]
Environmental Impact
Carbon emissions can be estimated using the
Machine Learning Impact calculator presented in
Lacoste et al. (2019).
- Hardware Type: GPU
- Hours used: Unmeasured
- Cloud Provider: Github
- Compute Region: [More Information Needed]
- Carbon Emitted: [More Information Needed]
Technical Specifications [optional]
Model Architecture and Objective
The model is built on the transformer architecture and aims to be a learning goal for AI scientists hoping to learn
about transformers, and how they work.
Compute Infrastructure
[More Information Needed]
Hardware
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Software
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Citation [optional]
BibTeX:
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APA:
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Glossary [optional]
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More Information [optional]
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Model Card Authors [optional]
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Model Card Contact
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