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Migrate model card from transformers-repo

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Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755
Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/krevas/finance-koelectra-base-generator/README.md

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+ ---
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+ language: ko
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+ ---
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+
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+ # 📈 Financial Korean ELECTRA model
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+
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+ Pretrained ELECTRA Language Model for Korean (`finance-koelectra-base-generator`)
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+
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+ > ELECTRA is a new method for self-supervised language representation learning. It can be used to
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+ > pre-train transformer networks using relatively little compute. ELECTRA models are trained to
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+ > distinguish "real" input tokens vs "fake" input tokens generated by another neural network, similar to
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+ > the discriminator of a GAN.
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+
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+ More details about ELECTRA can be found in the [ICLR paper](https://openreview.net/forum?id=r1xMH1BtvB)
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+ or in the [official ELECTRA repository](https://github.com/google-research/electra) on GitHub.
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+
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+ ## Stats
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+
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+ The current version of the model is trained on a financial news data of Naver news.
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+
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+ The final training corpus has a size of 25GB and 2.3B tokens.
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+
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+ This model was trained a cased model on a TITAN RTX for 500k steps.
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+
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+ ## Usage
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ fill_mask = pipeline(
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+ "fill-mask",
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+ model="krevas/finance-koelectra-base-generator",
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+ tokenizer="krevas/finance-koelectra-base-generator"
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+ )
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+
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+ print(fill_mask(f"내일 해당 종목이 대폭 {fill_mask.tokenizer.mask_token}할 것이다."))
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+ ```
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+
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+ # Huggingface model hub
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+
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+ All models are available on the [Huggingface model hub](https://huggingface.co/krevas).