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--- |
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language: |
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- ko |
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datasets: |
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- kyujinpy/KOR-OpenOrca-Platypus-v3 |
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library_name: transformers |
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pipeline_tag: text-generation |
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license: cc-by-nc-sa-4.0 |
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--- |
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# **Ko-PlatYi-6B** |
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<img src='./Ko-PlatYi.png' width=256> |
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## Model Details |
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**Model Developers** Kyujin Han (kyujinpy) |
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**Input** Models input text only. |
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**Output** Models generate text only. |
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**Model Architecture** |
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Ko-PlatYi-6B is an auto-regressive language model based on the Yi-34B transformer architecture. |
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**Blog Link** |
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Blog: [Coming soon...] |
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Github: [Coming soon...] |
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**Base Model** |
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[beomi/Yi-Ko-6B](https://huggingface.co/beomi/Yi-Ko-6B) |
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**Training Dataset** |
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[kyujinpy/KOR-OpenOrca-Platypus-v3](https://huggingface.co/datasets/kyujinpy/KOR-OpenOrca-Platypus-v3). |
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# **Model Benchmark** |
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## Open leaderboard |
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> Follow up as [link](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard). |
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| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | CommonGen-V2 | |
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| --- | --- | --- | --- | --- | --- | --- | |
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| Ko-PlatYi-6B-O | 49.00 | 43.52 | 53.59 | 47.47 | 41.01 | 59.39 | |
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| Ko-PlatYi-6B-kiwi | 48.75 | 41.98 | 53.61 | 46.10 | 38.30 | 63.75 | |
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| Ko-PlatYi-6B-gu | 48.76 | 42.75 | 54.00 | 44.66 | 41.22 | 61.16 | |
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| **Ko-PlatYi-6B** | 49.97 | 43.00 | 53.55 | 46.50 | 40.31 | 66.47 | |
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| Yi-Ko-6B | 48.79 | 41.04 | 53.39 | 46.28 | 41.64 | 61.63 |
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--- |
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## AI-Harness Evaluation |
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> AI-Harness evaluation; [link](https://github.com/Beomi/ko-lm-evaluation-harness) |
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| Model | BoolQ | Copa | HellaSwag | Sentineg | |
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| --- | --- | --- | --- | --- | |
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| | *Zero-shot* |||| |
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| Ko-PlatYi-6B-O | 0.3343 | 0.7687 | 0.4833 | 0.5794 | |
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| Ko-PlatYi-6B-kiwi | 0.3343 | 0.7665 | 0.4746 | **0.6248** | |
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| Ko-PlatYi-6B-gu | **0.7077** | **0.7696** | 0.4797 | 0.3979 | |
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| **Ko-PlatYi-6B** | 0.3343 | 0.7684 | **0.4917** | 0.5226 | |
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| Yi-Ko-6B | **0.7070** | 0.7696 | **0.5009** | 0.4044 | |
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--- |
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# Implementation Code |
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```python |
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### KO-Platypus |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import torch |
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repo = "kyujinpy/Ko-PlatYi-6B" |
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OpenOrca = AutoModelForCausalLM.from_pretrained( |
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repo, |
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return_dict=True, |
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torch_dtype=torch.float16, |
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device_map='auto' |
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) |
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OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo) |
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``` |
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