prince-canuma
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README.md
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# Model Summary
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<img src="llama-3-6B icon.jpeg" width="500" alt="Llama-3-6B"/>
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- Loss: 2.4942
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<!-- Provide a longer summary of what this model is. -->
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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:** [More Information Needed]
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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:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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## Model Description
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<!-- Provide a longer summary of what this model is. -->
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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:** [Prince Canuma](https://huggingface.co/prince-canuma)
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- **License:** MIT
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### Model Sources [optional]
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## Training Details
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### Training Data
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For continued pretrained, I extracted 1B tokens from [Huggingface's FineWeb CC-Main-2024-10](https://huggingface.co/datasets/HuggingFaceFW/fineweb#breakdown-by-dumpcrawl) slice.
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# Model Summary
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<img src="llama-3-6B icon.jpeg" width="500" alt="Llama-3-6B"/>
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Introducing the world's first Llama-3 base model with 6B parameters. This model is a pretrained version of [prince-canuma/Llama-3-6B-v0](https://huggingface.co/prince-canuma/Llama-3-6B-v0), which was created from Meta-Llama-3-8B using a technique called [downcycling](https://youtube.com/playlist?list=PLDn_JsyofyfTH5_5V1MNb8UYKxMl6IMNy&si=9hcOol4KHIgWThgt) .
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The model was continually pretrained on 1 billion tokens of English-only text from fineweb, achieving impressive results on the evaluation set:
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- Loss: 2.4942
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<!-- Provide a longer summary of what this model is. -->
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## Model Description
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<!-- Provide a longer summary of what this model is. -->
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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:** [Prince Canuma](https://huggingface.co/prince-canuma)
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- **Sponsored by:** General
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- **Model type:** Llama
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** MIT
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- **Pretrained from model:** prince-canuma/Llama-3-6B-v0
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### Model Sources [optional]
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## Training Details
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### Downcycling
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A technique that allows you to create new LLMs of diversa sizes from checkpoints of large pretrained models.
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You take a reference model (i.e., Llama-3-8B) and copy the weights of 24 layers out of 32 layers alongside embedding and prediction heads. Then you initialize a smaller target model with 24 layers and load those pretrained weights.
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This new model will most likely still output legible outputs, but for it to perform well you need continue the pretraining.
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### Training Data
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For continued pretrained, I extracted 1B tokens from [Huggingface's FineWeb CC-Main-2024-10](https://huggingface.co/datasets/HuggingFaceFW/fineweb#breakdown-by-dumpcrawl) slice.
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