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--- |
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license: llama3 |
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language: |
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- si |
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base_model: meta-llama/Meta-Llama-3-8B |
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library_name: transformers |
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--- |
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# Llama3 8B for Sinhala: 50 target vocabulary size + Align target vocabulary initialization + 2x2LS/MTP/512 training |
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This model is built on top of Llama3 8B adapted for Sinhala using 30K target language sentences sampled from CC-100. |
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## Model Details |
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* **Vocabulary**: This model has an additional 50 target vocabulary. |
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* **Target vocabulary initialization**: The target weights of the embedding and LM head were initialized using Align initialization. |
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* **Training**: This model was additionally pre-trained on 30K target language sentences sampled from CC-100. The training was conducted with the 2x2LS/MTP/512 strategies introduced in the paper. |
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## Model Description |
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- **Language:** Sinhala |
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- **License:** Llama 3 Community License Agreement |
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- **Fine-tuned from model:** meta-llama/Meta-Llama-3-8B |
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## Model Sources |
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- **Repository:** https://github.com/gucci-j/lowres-cve |
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- **Paper:** https://arxiv.org/abs/2406.11477 |
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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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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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model = AutoModelForCausalLM.from_pretrained( |
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"atsuki-yamaguchi/Llama-3-8B-si-30K-50-align" |
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) |
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tokenizer = AutoTokenizer.from_pretrained( |
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"atsuki-yamaguchi/Llama-3-8B-si-30K-50-align" |
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) |
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``` |
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