Instructions to use ethansimrm/opus_base_ailem_adaptified with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethansimrm/opus_base_ailem_adaptified with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ethansimrm/opus_base_ailem_adaptified") model = AutoModelForSeq2SeqLM.from_pretrained("ethansimrm/opus_base_ailem_adaptified", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ethansimrm/opus_base_ailem_adaptified: direct link, hf CLI and curl.
- Browser
- Download file 299 MB
-
https://huggingface.co/ethansimrm/opus_base_ailem_adaptified/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ethansimrm/opus_base_ailem_adaptified/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ethansimrm/opus_base_ailem_adaptified/resolve/main/pytorch_model.bin
299 MB
- Xet hash:
- cb816d1cd7734322102fe950073562702cb85f9fab198c277dbd495b3dce2718
- Size of remote file:
- 299 MB
- SHA256:
- 9d0774ab9476872adac62a2bdc9ae11a4ed42b28f1e5d93d8fb857405c3a50e3
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