Instructions to use retrieva-jp/bert-1.3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use retrieva-jp/bert-1.3b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="retrieva-jp/bert-1.3b", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("retrieva-jp/bert-1.3b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 134d9376156bb9f5702159cd22cbe324282951858d65ffed5e77e61b5d155c67
- Size of remote file:
- 2.6 GB
- SHA256:
- 994bd099f4bb0c9bab36ed16e1a8271f46f637de6b06e32fa1f29643d7b528c9
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