Instructions to use Davlan/mt5_base_eng_yor_mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/mt5_base_eng_yor_mt with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Davlan/mt5_base_eng_yor_mt") model = AutoModelForSeq2SeqLM.from_pretrained("Davlan/mt5_base_eng_yor_mt") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60d9abec51cd567fdc540ede076036fefb5643650a22a30c51023cdc8fa847c2
- Size of remote file:
- 2.33 GB
- SHA256:
- 8e686e989b8dbee3eedd4d02b5547dc7c9a902b218b0819160d58cc5b839c9f6
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