Create README.md

README.md

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+---
+license: llama3
+language:
+- my
+base_model: meta-llama/Meta-Llama-3-8B
+library_name: transformers
+---
+
+# LLaMA3-8B for Burmese: 5K target vocabulary size + Random target vocabulary initialization + T&B 2LS/MTP/512 training
+
+This model is built on top of LLaMA3-8B adapted for Burmese using 30K target language sentences sampled from CC-100.
+
+## Model Details
+
+* **Vocabulary**: This model has an additional 5K target vocabulary.  
+* **Target vocabulary initialization**: The target weights of the embedding and LM head were initialized using random initialization.  
+* **Training**: This model was additionally pre-trained on 30K target language sentences sampled from CC-100. The training was conducted with the T&B 2LS, MTP, and 512 strategies introduced in the paper.  
+
+### Model Description
+
+- **Language:** Burmese
+- **License:** Llama 3 Community License Agreement
+- **Finetuned from model:** meta-llama/Meta-Llama-3-8B
+
+### Model Sources
+
+- **Repository:** https://github.com/gucci-j/lowres-cve
+- **Paper:** https://arxiv.org/abs/2406.11477
+
+## How to Get Started with the Model
+Use the code below to get started with the model.
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained(
+    "atsuki-yamaguchi/Llama-3-8B-my-30K-5000-rand"
+)
+tokenizer = AutoTokenizer.from_pretrained(
+    "atsuki-yamaguchi/Llama-3-8B-my-30K-5000-rand"
+)
+```
+
+## Citation
+```
+TBA
+```