Instructions to use Kdogs/dapt_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kdogs/dapt_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Kdogs/dapt_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Kdogs/dapt_bert") model = AutoModelForMaskedLM.from_pretrained("Kdogs/dapt_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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klue/bert-base-sports-train_size4900000-epochs1-batch32-noSplit-noNSP
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klue/bert-base-sports-train_size6919-epochs3-batch32-noSplit-NSP
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klue/bert-base-sports-train_size70000-epochs5-batch16-Split-noNSP
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klue/bert-base-sports-train_size6919-epochs3-batch16-noSplit-NSP
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klue/bert-base, split O, sports data, batch 16
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klue/roberta-sports-noNSP
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change kcbert + IT domain + with NSP
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DAPT Kcbert
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DAPT KLUE
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