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

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.

[More Information Needed]

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]

[More Information Needed]

Evaluation

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

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]

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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