Instructions to use lighteternal/SSE-TUC-mt-en-el-lowercase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lighteternal/SSE-TUC-mt-en-el-lowercase with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="lighteternal/SSE-TUC-mt-en-el-lowercase")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lighteternal/SSE-TUC-mt-en-el-lowercase") model = AutoModelForSeq2SeqLM.from_pretrained("lighteternal/SSE-TUC-mt-en-el-lowercase") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8eb7cef62bb4c770acd21db0b92037f4c6e63640cd75c9815f70b4de235a38f
- Size of remote file:
- 173 MB
- SHA256:
- 04df29cda5952138f6dd7e03361f0e3cb1219625791b7c61f5b8475de20f2311
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