Instructions to use JunHwi/kmhas_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JunHwi/kmhas_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JunHwi/kmhas_binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JunHwi/kmhas_binary") model = AutoModelForSequenceClassification.from_pretrained("JunHwi/kmhas_binary") - Notebooks
- Google Colab
- Kaggle
add training_args.bin
Browse files- training_args.bin +3 -0
training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:0a1d846a75c21826ff344e9b62dfb775be406202e0f4524d00c83a527aaa63d8
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size 3311
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