Instructions to use kouohhashi/roberta_ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kouohhashi/roberta_ja with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kouohhashi/roberta_ja")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kouohhashi/roberta_ja") model = AutoModel.from_pretrained("kouohhashi/roberta_ja", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from kouohhashi/roberta_ja: direct link, hf CLI and curl.
- Browser
- Download file 272 MB
-
https://huggingface.co/kouohhashi/roberta_ja/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://kouohhashi/roberta_ja/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/kouohhashi/roberta_ja/resolve/main/flax_model.msgpack
272 MB
- Xet hash:
- 168072b45337c54d9d6380edfdae6f9b2c44d7d3fc9cb2bcdb3f123965387298
- Size of remote file:
- 272 MB
- SHA256:
- 9e8f8ade365f6aa912f6994385bfc486485f94edccb407e746bf260255091adf
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