Instructions to use rinna/japanese-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rinna/japanese-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="rinna/japanese-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("rinna/japanese-roberta-base") model = AutoModelForMaskedLM.from_pretrained("rinna/japanese-roberta-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rinna/japanese-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/rinna/japanese-roberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rinna/japanese-roberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rinna/japanese-roberta-base/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- d229e3d5e95249409ab1ac5d46a17922d84dd7c3f7b9303d453111af61068a64
- Size of remote file:
- 443 MB
- SHA256:
- 0f8b82568ffba99a6a4ecdbec6951a64b9dd51e07fbf7b9d8f09352a54f0a668
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