Instructions to use ethansimrm/opus_base_lsp_simple_wce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethansimrm/opus_base_lsp_simple_wce with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ethansimrm/opus_base_lsp_simple_wce") model = AutoModelForSeq2SeqLM.from_pretrained("ethansimrm/opus_base_lsp_simple_wce", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ethansimrm/opus_base_lsp_simple_wce: direct link, hf CLI and curl.
- Browser
- Download file 3.77 kB
-
https://huggingface.co/ethansimrm/opus_base_lsp_simple_wce/resolve/main/training_args.bin
- Command line
-
hf download hf://ethansimrm/opus_base_lsp_simple_wce/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ethansimrm/opus_base_lsp_simple_wce/resolve/main/training_args.bin
3.77 kB
- Xet hash:
- bf9a09718e6a6f121bc0c1f579577580ff8d0a549c12df80e3d235ab866d9533
- Size of remote file:
- 3.77 kB
- SHA256:
- 3d0c9bc1e2fddfe046f1ac2f45049ae2699b59aa26664e5ff16c8e4b40205ce1
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