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]
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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
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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Model Card Authors [optional]
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Model Card Contact
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