atsuki-yamaguchi
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README.md
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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: 500 target vocabulary size + Align target vocabulary initialization + T&B2LS/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 500 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 T&B2LS/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-500-align"
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)
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tokenizer = AutoTokenizer.from_pretrained(
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"atsuki-yamaguchi/Llama-3-8B-si-30K-500-align"
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)
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```
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