Instructions to use ethansimrm/opus_big_lsp_simple_wce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethansimrm/opus_big_lsp_simple_wce with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ethansimrm/opus_big_lsp_simple_wce") model = AutoModelForSeq2SeqLM.from_pretrained("ethansimrm/opus_big_lsp_simple_wce", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from ethansimrm/opus_big_lsp_simple_wce: direct link, hf CLI and curl.
- Browser
- Download file 1.85 GB
-
https://huggingface.co/ethansimrm/opus_big_lsp_simple_wce/resolve/main/optimizer.pt
- Command line
-
hf download hf://ethansimrm/opus_big_lsp_simple_wce/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ethansimrm/opus_big_lsp_simple_wce/resolve/main/optimizer.pt
1.85 GB
- Xet hash:
- a6f70b346ad9887520ecd0abf6d6329fe5958b089e0c1acca64bf96d07e41bcb
- Size of remote file:
- 1.85 GB
- SHA256:
- fe39336a53d22b211b3a4841695d4cce6332444a3686f8389e10d6d9dc99009d
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