Instructions to use Formzu/bart-base-japanese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Formzu/bart-base-japanese with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Formzu/bart-base-japanese") model = AutoModelForSeq2SeqLM.from_pretrained("Formzu/bart-base-japanese", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Formzu/bart-base-japanese: direct link, hf CLI and curl.
- Browser
- Download file 502 MB
-
https://huggingface.co/Formzu/bart-base-japanese/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Formzu/bart-base-japanese/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Formzu/bart-base-japanese/resolve/main/pytorch_model.bin
502 MB
- Xet hash:
- e04ed5ddc659adebf4cd07220688ff6958b014dc2a3d8dd207582ed5af1cf965
- Size of remote file:
- 502 MB
- SHA256:
- 74367555daf7ab2ed66635f49f84bde097db57d11cb0c6c293410645a0f3f34f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.