---
license: cc-by-4.0
language:
- en
base_model:
- Aobangaming/Aoban1.1A-Refined
new_version: Aobangaming/Aoban1.1A-Refined
pipeline_tag: text-generation
tags:
- model
- text-generation
---
# 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](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).

## 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]

<!-- Provide the basic links for the model. -->

- **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

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

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.

https://github.com/AobanZ-MinecraftYoutuber/Aoban-1.1A-Refined

## Training Details

The model is trained on over 500 sentences, varying differently.

### Training Data



[More Information Needed]

### Training Procedure

<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->

#### Preprocessing [optional]

[More Information Needed]


#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->

[More Information Needed]

## Evaluation

<!-- This section describes the evaluation protocols and provides the results. -->

### Testing Data, Factors & Metrics

#### Testing Data

<!-- This should link to a Dataset Card if possible. -->

[More Information Needed]

#### Factors

<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->

[More Information Needed]

#### Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->

[More Information Needed]

### Results

[More Information Needed]

#### Summary



## Model Examination [optional]

<!-- Relevant interpretability work for the model goes here -->

[More Information Needed]

## Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **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

[More Information Needed]

#### Software

[More Information Needed]

## Citation [optional]

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

[More Information Needed]

**APA:**

[More Information Needed]

## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->

[More Information Needed]

## More Information [optional]

[More Information Needed]

## Model Card Authors [optional]

[More Information Needed]

## Model Card Contact

[More Information Needed]