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--- |
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license: llama2 |
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language: |
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- si |
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base_model: meta-llama/Llama-2-7b-hf |
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library_name: transformers |
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--- |
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# Llama2 7B for Sinhala: 100 target vocabulary size + Random target vocabulary initialization |
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This model is built on top of Llama2 7B 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 100 target vocabulary. |
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* **Target vocabulary initialization**: The target weights of the embedding and LM head were initialized using Random initialization. |
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* **Training**: This model was additionally pre-trained on 30K target language sentences sampled from CC-100. |
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## Model Description |
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- **Language:** Sinhala |
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- **License:** Llama 2 Community License Agreement |
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- **Fine-tuned from model:** meta-llama/Llama-2-7b-hf |
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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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from peft import PeftModelForCausalLM |
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model = AutoModelForCausalLM.from_pretrained( |
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"atsuki-yamaguchi/Llama-2-7b-hf-si-30K-rand" |
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) |
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model = PeftModelForCausalLM.from_pretrained( |
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model, |
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"atsuki-yamaguchi/Llama-2-7b-hf-si-30K-rand" |
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) |
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model = model.merge_and_unload() |
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tokenizer = AutoTokenizer.from_pretrained( |
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"atsuki-yamaguchi/Llama-2-7b-hf-si-30K-rand" |
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) |
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``` |
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