Instructions to use ethansimrm/opus_base_wce_random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethansimrm/opus_base_wce_random with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ethansimrm/opus_base_wce_random") model = AutoModelForSeq2SeqLM.from_pretrained("ethansimrm/opus_base_wce_random", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ethansimrm/opus_base_wce_random: direct link, hf CLI and curl.
- Browser
- Download file 299 MB
-
https://huggingface.co/ethansimrm/opus_base_wce_random/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ethansimrm/opus_base_wce_random/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ethansimrm/opus_base_wce_random/resolve/main/pytorch_model.bin
299 MB
- Xet hash:
- ac96e010c98a153778c69a60fe0c32df5a6aab4e6d7de07698b47b33697884f5
- Size of remote file:
- 299 MB
- SHA256:
- 2dd20a16fdf42880102fb083c138ba0843a36bbb2779a8bfe8fa457490a91e88
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.