Instructions to use dbmdz/convbert-base-turkish-mc4-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbmdz/convbert-base-turkish-mc4-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbmdz/convbert-base-turkish-mc4-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbmdz/convbert-base-turkish-mc4-cased") model = AutoModelForMaskedLM.from_pretrained("dbmdz/convbert-base-turkish-mc4-cased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- de0923c354cf37c99552d19d54e12588af7abc644264eb5634d21de180cf8fa9
- Size of remote file:
- 427 MB
- SHA256:
- 95f6b66a4a2d574ca04b4bb87a1c606e230d3c7e8e6fcb8d31f813f20c5c26cf
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