---
language:
- ko
- en
pipeline_tag: text-generation
inference: false
tags:
- solar
- mistral
- pytorch
- solar-ko
library_name: transformers
license: apache-2.0
---

**Update Log**

- 2024.05.16: Released Solar-Ko-Recovery

# **Solar-Ko-Recovery** ⭐🇰🇷🇺🇸

Solar-Ko-Recovery aimed to recover Solar's capability on Korean with re-arrange of Embeddings and LM head, featuring an expanded vocabulary and the inclusion of a Korean+English corpus for enhanced representation. 

## Model Details

**Model Developers:** Junbum Lee (Beomi)

**Variations:** Solar-Ko-Recovery is available with one parameter sizes — 10.8B.

**Input:** The model accepts only text input.

**Output:** The model produces text output exclusively.

**Model Architecture:** 

Solar-Ko-Recovery is an auto-regressive language model that leverages an optimized transformer architecture derived from Llama-2.

| |Training Data|Parameters|Content Length|GQA|Tokens|Learning Rate|
|---|---|---|---|---|---|---|
|Solar-Ko-Recovery|*A curated mix of Korean+English Corpora*|10.8B|4k|O|>30B*|5e<sup>-5</sup>|

**Vocab Expansion**

Vocab expansion is conducted on edited [upstage/solar-1-mini-tokenizer](https://huggingface.co/upstage/solar-1-mini-tokenizer), which is superset of Solar tokenizer.

| Model Name | Vocabulary Size | Description | 
| --- | --- | --- |
| Original Solar | 32000 | Sentencepiece BPE |
| **solar-1-mini-tokenizer** | 64000 | Sentencepiece BPE. Added Ko/JP vocabs |

**Tokenizing "안녕하세요, 오늘은 날씨가 좋네요."**

- SOLAR-10.7B: 26 tokens
- Solar-Ko-Recovery: 7 tokens

| Model | Tokens |
| --- | --- |
| SOLAR-10.7B | `['▁', '안', '<0xEB>', '<0x85>', '<0x95>', '하', '세', '요', ',', '▁', '오', '<0xEB>', '<0x8A>', '<0x98>', '은', '▁', '날', '<0xEC>', '<0x94>', '<0xA8>', '가', '▁', '좋', '네', '요', '.']` |
| Solar-Ko-Recovery | `['▁안녕하세요', ',', '▁오늘은', '▁날씨가', '▁좋', '네요', '.']` |

**Tokenizing "Meet 10.7B Solar: Elevating Performance with Upstage Depth UP Scaling!"**

- SOLAR-10.7B: 22 tokens
- Solar-Ko-Recovery: 22 tokens

| Model | Tokens |
| --- | --- |
| SOLAR-10.7B | `['▁Meet', '▁', '1', '0', '.', '7', 'B', '▁Solar', ':', '▁E', 'lev', 'ating', '▁Performance', '▁with', '▁Up', 'stage', '▁Dep', 'th', '▁UP', '▁Scal', 'ing', '!']` |
| Solar-Ko-Recovery | `['▁Meet', '▁', '1', '0', '.', '7', 'B', '▁Solar', ':', '▁E', 'lev', 'ating', '▁Performance', '▁with', '▁Up', 'stage', '▁Dep', 'th', '▁UP', '▁Scal', 'ing', '!']` |

# LICENSE

Apache 2.0

# **Model Benchmark**

## LM Eval Harness - Korean

- Used EleutherAI's [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness)
- 5-shot scores

TBD

## Citation

TBD

## Acknowledgements

- Training support was provided by the [TPU Research Cloud](https://sites.research.google/trc/) program.