Instructions to use ethansimrm/opus_big_wce_adaptified with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethansimrm/opus_big_wce_adaptified with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ethansimrm/opus_big_wce_adaptified") model = AutoModelForSeq2SeqLM.from_pretrained("ethansimrm/opus_big_wce_adaptified", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ethansimrm/opus_big_wce_adaptified: direct link, hf CLI and curl.
- Browser
- Download file 923 MB
-
https://huggingface.co/ethansimrm/opus_big_wce_adaptified/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ethansimrm/opus_big_wce_adaptified/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ethansimrm/opus_big_wce_adaptified/resolve/main/pytorch_model.bin
923 MB
- Xet hash:
- cedb4e6aff30a518b17b20adfb119b69950d4ec560f6fa3def78f49d663ca9b7
- Size of remote file:
- 923 MB
- SHA256:
- c73120ed5f0886eb579215ffef18fdc6e90ab5b7c32a765c31c5c58611905824
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