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--- |
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language: ko |
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license: cc-by-nc-sa-4.0 |
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tags: |
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- gpt2 |
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--- |
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# Model Card for kogpt2-base-v2 |
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# Model Details |
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## Model Description |
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[GPT-2](https://openai.com/blog/better-language-models/)λ μ£Όμ΄μ§ ν
μ€νΈμ λ€μ λ¨μ΄λ₯Ό μ μμΈ‘ν μ μλλ‘ νμ΅λ μΈμ΄λͺ¨λΈμ΄λ©° λ¬Έμ₯ μμ±μ μ΅μ ν λμ΄ μμ΅λλ€. `KoGPT2`λ λΆμ‘±ν νκ΅μ΄ μ±λ₯μ 극볡νκΈ° μν΄ 40GB μ΄μμ ν
μ€νΈλ‘ νμ΅λ νκ΅μ΄ λμ½λ(`decoder`) μΈμ΄λͺ¨λΈμ
λλ€. |
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- **Developed by:** SK Telecom |
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- **Shared by [Optional]:** SK Telecom |
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- **Model type:** Text Generation |
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- **Language(s) (NLP):** Korean |
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- **License:** cc-by-nc-sa-4.0 |
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- **Parent Model:** GPT-2 |
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- **Resources for more information:** |
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- [GitHub Repo](https://github.com/SKT-AI/KoGPT2/tree/master) |
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- [Model Demo Space](https://huggingface.co/spaces/gogamza/kogpt2-base-v2) |
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# Uses |
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## Direct Use |
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This model can be used for the task of Text Generation |
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## Downstream Use [Optional] |
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More information needed. |
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## Out-of-Scope Use |
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The model should not be used to intentionally create hostile or alienating environments for people. |
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# Bias, Risks, and Limitations |
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Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. |
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## Recommendations |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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# Training Details |
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## Training Data |
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The model authors also note in the [GitHub Repo](https://github.com/SKT-AI/KoGPT2/tree/master): |
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[`tokenizers`](https://github.com/huggingface/tokenizers) ν¨ν€μ§μ `Character BPE tokenizer`λ‘ νμ΅λμμ΅λλ€. |
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μ¬μ ν¬κΈ°λ 51,200 μ΄λ©° λνμ μμ£Ό μ°μ΄λ μλμ κ°μ μ΄λͺ¨ν°μ½, μ΄λͺ¨μ§ λ±μ μΆκ°νμ¬ ν΄λΉ ν ν°μ μΈμ λ₯λ ₯μ μ¬λ Έμ΅λλ€. |
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> π, π, π, π
, π€£, .. , `:-)`, `:)`, `-)`, `(-:`... |
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[νκ΅μ΄ μν€ λ°±κ³Ό](https://ko.wikipedia.org/) μ΄μΈ, λ΄μ€, [λͺ¨λμ λ§λμΉ v1.0](https://corpus.korean.go.kr/), [μ²μλ κ΅λ―Όμ²μ](https://github.com/akngs/petitions) λ±μ λ€μν λ°μ΄ν°κ° λͺ¨λΈ νμ΅μ μ¬μ©λμμ΅λλ€. |
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## Training Procedure |
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### Preprocessing |
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More information needed |
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### Speeds, Sizes, Times |
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| Model | # of params | Type | # of layers | # of heads | ffn_dim | hidden_dims | |
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|--------------|:----:|:-------:|--------:|--------:|--------:|--------------:| |
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| `kogpt2-base-v2` | 125M | Decoder | 12 | 12 | 3072 | 768 | |
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# Evaluation |
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## Testing Data, Factors & Metrics |
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### Testing Data |
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More information needed |
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### Factors |
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More information needed |
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### Metrics |
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More information needed |
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## Results |
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### Classification or Regression |
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| | [NSMC](https://github.com/e9t/nsmc)(acc) | [KorSTS](https://github.com/kakaobrain/KorNLUDatasets)(spearman) | |
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| **KoGPT2 2.0** | 89.1 | 77.8 | |
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# Model Examination |
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More information needed |
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# Environmental Impact |
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
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- **Hardware Type:** More information needed |
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- **Hours used:** More information needed |
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- **Cloud Provider:** More information needed |
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- **Compute Region:** More information needed |
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- **Carbon Emitted:** More information needed |
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# Technical Specifications [optional] |
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## Model Architecture and Objective |
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More information needed |
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## Compute Infrastructure |
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More information needed |
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### Hardware |
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More information needed |
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### Software |
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More information needed. |
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# Citation |
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**BibTeX:** |
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More information needed |
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# Glossary [optional] |
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More information needed |
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# More Information [optional] |
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More information needed |
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# Model Card Authors [optional] |
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SK Telecom in collaboration with Ezi Ozoani and the Hugging Face team |
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# Model Card Contact |
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The model authors also note in the [GitHub Repo](https://github.com/SKT-AI/KoGPT2/tree/master) |
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> `KoGPT2` κ΄λ ¨ μ΄μλ [μ΄κ³³](https://github.com/SKT-AI/KoGPT2/issues)μ μ¬λ €μ£ΌμΈμ. |
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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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<details> |
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<summary> Click to expand </summary> |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("skt/kogpt2-base-v2") |
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model = AutoModelForCausalLM.from_pretrained("skt/kogpt2-base-v2") |
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``` |
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</details> |
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