Model Card for Model ID

Meme++ generator.

Model Details

Model Description

This is a tiny LLaMA model trained from scratch for 31000 steps (253952000 tokens) out of i forgor :skull:.

• Developed by: mrsteyk
• Model type: LLaMA
• Language(s) (NLP): English
• License: WTFPL

Model Sources [optional]

• Repository: maybe someday

Uses

This was intended for Meme++ character chard generation, trained a small demo.

Direct Use

Random Meme++ card generation.

Out-of-Scope Use

CSAM related stuff.

Bias, Risks, and Limitations

This model was trained on a randomly scraped DataSet, I tried filtering as much as I could automatically, it might still try to generate kids because people are fucking weirdos.

Recommendations

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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.

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Training Details

Training Data

Meme++ character definition taken off the internet.

Training Procedure

This was trained using lit-llama based model code and pytorch-lightning CLI based trainer code.

Training Hyperparameters

• Training regime: fp32
• Optimizer and LR: DeepSpeed FusedAdamW with 1e-5

Speeds, Sizes, Times [optional]

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Evaluation

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Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

W&B run

Model Examination [optional]

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Environmental Impact

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

• Hardware Type: 1050 Ti Mobile
• Hours used: ~6
• Cloud Provider: Local Machine(C)(TM)
• Compute Region: RU
• Carbon Emitted: 450kg

Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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BibTeX:

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APA:

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Glossary [optional]

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