Instructions to use suzuki-2001/BERT-K8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suzuki-2001/BERT-K8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="suzuki-2001/BERT-K8")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("suzuki-2001/BERT-K8") model = AutoModelForMaskedLM.from_pretrained("suzuki-2001/BERT-K8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9992171e60168db72c41a46e95fc3f99eee1852c30d7767569aa27b435d1bb18
- Size of remote file:
- 4.86 kB
- SHA256:
- d508bca6099540f2f318fa6ee0110c93e6175e02283d6a981568998303987d89
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