Update README.md

README.md

@@ -27,7 +27,8 @@ SambaLingo-Japanese-Base is a pretrained Bi-lingual Japanese and English model t
 - **Model type:** Language Model
 - **Language(s):** Japanese, English
 - **Finetuned from model:** [Llama 2](https://huggingface.co/meta-llama/Llama-2-7b-hf)
-- **Blog Post**: Will be released soon!
+- **Paper:** [SambaLingo: Teaching Large Language Models New Languages](https://arxiv.org/abs/2404.05829)
+- **Blog Post**: [SambaLingo Open Source Language Experts](https://sambanova.ai/blog/sambalingo-open-source-language-experts)
 
 ## Getting Started
 
@@ -52,17 +53,7 @@ All pre-training is done on the [Cultura-X](https://huggingface.co/datasets/uonl
 We extended the vocabulary of the base llama model from 32,000 tokens to 57,000 tokens by adding up to 25,000 non-overlapping tokens from the new language.
 
 ## Evaluation
-|| SambaLingo-Japanese-Base     | ELYZA-japanese-Llama-2-7b-7b | bloom-7b1 | xglm-7.5B | mGPT-13B |        
-|------------------------------|------------------------------|-----------|-----------|----------|--------|
-| Perplexity (Lower Is Better) | **1.559**                        | 1.754     | 2.216     | 1.775    | 2.349  |
-| FLORES en->ja (8 shot, CHRF) | **0.281**                        | 0.250     | 0.056     | 0.156    | 0.111  |
-| FLORES ja->en (8 shot, CHRF) | **0.495**                        | 0.436     | 0.262     | 0.369    | 0.297  |
-| FLORES en->ja (8 shot, BLEU) | 0.000                        | 0.000     | 0.000     | 0.000    | 0.000  |
-| FLORES ja->en (8 shot, BLEU) | **0.184**                        | 0.144     | 0.043     | 0.084    | 0.036  |
-| Belebele (3 shot)            | 36.56%                       | **53.67%**    | 26.67%    | 24.00%   | 22.89% |
-| SIB-200 (3 shot)             | 68.63%                       | **74.02%**    | 60.29%    | 60.78%   | 41.18% |
-| PAWS-X                       | 46.80%                       | 50.50%   | 45.40%    | **51.95%**    | 45.20% |
-| XWinograd (0 shot)           | 76.64%                       | **77.58%**    | 58.92%    | 64.96%   | 57.77% |
+For evaluation results see our paper: [SambaLingo: Teaching Large Language Models New Languages](https://arxiv.org/abs/2404.05829)
 
 ## Uses
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
@@ -105,12 +96,12 @@ We would like to give a special thanks to the following groups:
 
 ## Cite SambaLingo
 ```
-@software{sambalingo,
-  title = {{SambaLingo: Open Source Language Experts}},
-  author = {SambaNova Systems},
-  url = {https://huggingface.co/sambanovasystems/SambaLingo-Japanese-Base}
-  month = {2},
-  year = {2024},
-  version = {1.0},
+@misc{csaki2024sambalingo,
+      title={SambaLingo: Teaching Large Language Models New Languages}, 
+      author={Zoltan Csaki and Bo Li and Jonathan Li and Qiantong Xu and Pian Pawakapan and Leon Zhang and Yun Du and Hengyu Zhao and Changran Hu and Urmish Thakker},
+      year={2024},
+      eprint={2404.05829},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
 }
 ```