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:
- cf30bd05f6b08b63b52a15b97470812b05f039b0349c93efc14d349ad6452c5b
- Size of remote file:
- 310 MB
- SHA256:
- 8c658eaf9d2256f34a6b5b8f4f71de12a8670b762c150c1b52f05ba2417376a4
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