Instructions to use kisti/korscideberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kisti/korscideberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kisti/korscideberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kisti/korscideberta") model = AutoModelForMaskedLM.from_pretrained("kisti/korscideberta") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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์ณ๋ฅผ ๊ธฐ๋ฐ์ผ๋ก, ๋
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### Downstream Use
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## Load Huggingface model directly
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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1. ํํ์ ๋ถ์๊ธฐ(Mecab) ๋ฑ ์ค์น ํ์ - KorSciDeBERTa ํ๊ฒฝ์ค์น+ํ์ธํ๋.pdf ์ฐธ์กฐ
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</code></pre>
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## KorSciDeBERTa native code
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KorSciDeBERTa ํ๊ฒฝ์ค์น+ํ์ธํ๋.pdf ์ฐธ์กฐ
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<pre><code>
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### Downstream Use
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### Load Huggingface model directly
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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1. ํํ์ ๋ถ์๊ธฐ(Mecab) ๋ฑ ์ค์น ํ์ - KorSciDeBERTa ํ๊ฒฝ์ค์น+ํ์ธํ๋.pdf ์ฐธ์กฐ
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</code></pre>
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### KorSciDeBERTa native code
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KorSciDeBERTa ํ๊ฒฝ์ค์น+ํ์ธํ๋.pdf ์ฐธ์กฐ
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<pre><code>
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