Instructions to use Davlan/mt5_base_yor_eng_mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/mt5_base_yor_eng_mt with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Davlan/mt5_base_yor_eng_mt") model = AutoModelForSeq2SeqLM.from_pretrained("Davlan/mt5_base_yor_eng_mt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d03776f76582fb900166a817eee860b5dd9af03c0932d6ed93c305cc3ebbcb88
- Size of remote file:
- 2.33 GB
- SHA256:
- 4b4979a822497b043e28f59ed760b5adc4248b003a6e9d9927dafffd98492b33
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