Instructions to use nlp-waseda/roberta-base-japanese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlp-waseda/roberta-base-japanese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlp-waseda/roberta-base-japanese")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nlp-waseda/roberta-base-japanese") model = AutoModelForMaskedLM.from_pretrained("nlp-waseda/roberta-base-japanese", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nlp-waseda/roberta-base-japanese: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/nlp-waseda/roberta-base-japanese/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nlp-waseda/roberta-base-japanese/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nlp-waseda/roberta-base-japanese/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- b16b68863ea3c41124cc6bb394a187afdf26762eee61e77b8a2f3a2e51acc770
- Size of remote file:
- 443 MB
- SHA256:
- b26a40bee61b7ab95739d7a0839e29a66cba82343b509bd4008e49d7577e9c77
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