Instructions to use KooAI/KooBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KooAI/KooBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="KooAI/KooBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("KooAI/KooBERT") model = AutoModelForMaskedLM.from_pretrained("KooAI/KooBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad1590439e61a7fd15169d15c5f9b66529577033dc8c5c24ab7a390e6f921e6c
- Size of remote file:
- 737 MB
- SHA256:
- 1e528f093db26d5c350a82ab3a6d2797f672ad7f2738d9de1268f45d47f09548
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