Instructions to use Davlan/oyo-mt-bert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/oyo-mt-bert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Davlan/oyo-mt-bert-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Davlan/oyo-mt-bert-large") model = AutoModelForMaskedLM.from_pretrained("Davlan/oyo-mt-bert-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72674845c8dded3d980dc1739987414e315e491c49a8c49bb12fa3e025ef9505
- Size of remote file:
- 1.35 GB
- SHA256:
- 5ee37b2215fe50408b752985b75381f3876d46728c6148208134e7c13728e7e7
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