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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:**
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:**
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- **Language(s) (NLP):**
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- **License:**
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- **Finetuned from model [optional]:**
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:**
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** shng2025
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** LLM, ~150M
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- **Language(s) (NLP):** English, Python
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- **License:** mit
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- **Finetuned from model [optional]:** gpt2 (i think) // Based on Codeparrot
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** https://github.com/Ice-Citron/GPTesla
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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This is my preliminary/first model trained based on teachings provided on O'reilly's transformer book. The idea is for this book to guide and teach me on the workflows of training a transformer that's based on CodeParrot. Before I move on and start conducting research for my CS EE. Likely on different ways to optimise how to train transformers from scratch.
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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