Instructions to use ethansimrm/opus_base_wce_adaptified with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethansimrm/opus_base_wce_adaptified with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ethansimrm/opus_base_wce_adaptified") model = AutoModelForSeq2SeqLM.from_pretrained("ethansimrm/opus_base_wce_adaptified", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ethansimrm/opus_base_wce_adaptified: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/ethansimrm/opus_base_wce_adaptified/resolve/main/training_args.bin
- Command line
-
hf download hf://ethansimrm/opus_base_wce_adaptified/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ethansimrm/opus_base_wce_adaptified/resolve/main/training_args.bin
3.77 kB
- Xet hash:
- 6d4a416e0b75a127192c8370f369d67fc2b80e10a97d84ecb8dfca3dd4529299
- Size of remote file:
- 3.77 kB
- SHA256:
- 00dba6608fa8aeace5d4d7a700208219e0f9dc795287f71cf75349dfe01fd209
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