Instructions to use muibk/tatoeba_emea_20k_en-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muibk/tatoeba_emea_20k_en-de with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("muibk/tatoeba_emea_20k_en-de") model = AutoModelForSeq2SeqLM.from_pretrained("muibk/tatoeba_emea_20k_en-de") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f06e0cf6cfe3120a7cd53d8241898206628a6b08591849146e34ef666c885690
- Size of remote file:
- 3.64 kB
- SHA256:
- 2cc0386eb1d635494254e08c4570d3561ea2f16f7b72b31f1beda5bf724dc5eb
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