memepp-llama-512v-6l-8h-256e

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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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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APA:

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Glossary [optional]

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