Instructions to use dbmdz/convbert-base-turkish-mc4-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbmdz/convbert-base-turkish-mc4-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbmdz/convbert-base-turkish-mc4-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbmdz/convbert-base-turkish-mc4-uncased") model = AutoModelForMaskedLM.from_pretrained("dbmdz/convbert-base-turkish-mc4-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8ce4f79338315d36e83c676a90db7e49a5eca5b7c12aa2bdf12587c6232f8d9
- Size of remote file:
- 427 MB
- SHA256:
- 2ec9f8575c23662aa0b4695d32e5a7619d64414723eb9cc9b08b9b4dba4e13b5
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