Instructions to use LDKSolutions/KR-cryptodeberta-v2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LDKSolutions/KR-cryptodeberta-v2-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LDKSolutions/KR-cryptodeberta-v2-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LDKSolutions/KR-cryptodeberta-v2-base") model = AutoModelForSequenceClassification.from_pretrained("LDKSolutions/KR-cryptodeberta-v2-base") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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license: apache-2.0
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Korean Pre-Trained Crypto DeBERTa model fine-tuned on BTC sentiment classification dataset.
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For more details, check our work [CBITS: Crypto BERT Incorporated Trading System](https://ieeexplore.ieee.org/document/10014986) on IEEE Access.
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