Instructions to use VRLLab/TurkishBERTweet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VRLLab/TurkishBERTweet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="VRLLab/TurkishBERTweet")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("VRLLab/TurkishBERTweet") model = AutoModelForMaskedLM.from_pretrained("VRLLab/TurkishBERTweet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7fad1d0595360d884502fd3e791452e72a75a2ac64c9a569bb5b807c40fb2210
- Size of remote file:
- 652 MB
- SHA256:
- 5fdbc361f60c5f82c9f3b63e163c94cb36f8e08caa60370c958d7741339226fd
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