Instructions to use kz/mt5base-finetuned-ECC-japanese-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kz/mt5base-finetuned-ECC-japanese-small with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kz/mt5base-finetuned-ECC-japanese-small") model = AutoModelForSeq2SeqLM.from_pretrained("kz/mt5base-finetuned-ECC-japanese-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kz/mt5base-finetuned-ECC-japanese-small: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/kz/mt5base-finetuned-ECC-japanese-small/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kz/mt5base-finetuned-ECC-japanese-small/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kz/mt5base-finetuned-ECC-japanese-small/resolve/main/pytorch_model.bin
2.33 GB
- Xet hash:
- b6a2949c31169bedad11f59f84068b73d39f21d1a81e76a2e1d95675b1baa9fd
- Size of remote file:
- 2.33 GB
- SHA256:
- 33cf2c58c5836e4336afac68908ee401b96094834b92cec6f8496a10225309a9
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