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--- |
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license: wtfpl |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- llama |
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- w++ |
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- meme++ |
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- tiny |
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--- |
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# Model Card for Model ID |
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Meme++ generator. |
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## Model Details |
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### Model Description |
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This is a tiny LLaMA model trained from scratch for 31000 steps (253952000 tokens) out of `i forgor :skull:`. |
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- **Developed by:** mrsteyk |
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- **Model type:** LLaMA |
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- **Language(s) (NLP):** English |
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- **License:** WTFPL |
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### Model Sources [optional] |
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- **Repository:** maybe someday |
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## Uses |
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This was intended for Meme++ character chard generation, trained a small demo. |
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### Direct Use |
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Random Meme++ card generation. |
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### Out-of-Scope Use |
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CSAM related stuff. |
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## Bias, Risks, and Limitations |
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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. |
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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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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. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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Meme++ character definition taken off the internet. |
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### Training Procedure |
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This was trained using `lit-llama` based model code and `pytorch-lightning` CLI based trainer code. |
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#### Training Hyperparameters |
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- **Training regime:** fp32 |
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- **Optimizer and LR:** DeepSpeed FusedAdamW with 1e-5 |
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#### Speeds, Sizes, Times [optional] |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
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[More Information Needed] |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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<!-- This should link to a Data Card if possible. --> |
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[More Information Needed] |
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#### Factors |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
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[More Information Needed] |
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#### Metrics |
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<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
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[More Information Needed] |
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### Results |
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[More Information Needed] |
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#### Summary |
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[W&B run](https://wandb.ai/mrsteyk/memepp-llama/runs/44e3aut4) |
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## Model Examination [optional] |
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<!-- Relevant interpretability work for the model goes here --> |
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[More Information Needed] |
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## Environmental Impact |
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
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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). |
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- **Hardware Type:** 1050 Ti Mobile |
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- **Hours used:** ~6 |
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- **Cloud Provider:** Local Machine(C)(TM) |
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- **Compute Region:** RU |
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- **Carbon Emitted:** ~~450kg~~ |
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## Technical Specifications [optional] |
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### Model Architecture and Objective |
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[More Information Needed] |
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### Compute Infrastructure |
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[More Information Needed] |
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#### Hardware |
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[More Information Needed] |
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#### Software |
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[More Information Needed] |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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## Glossary [optional] |
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> |
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[More Information Needed] |
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## More Information [optional] |
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[More Information Needed] |
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## Model Card Authors [optional] |
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[More Information Needed] |
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## Model Card Contact |
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[More Information Needed] |
