Instructions to use dbmdz/bert-base-turkish-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbmdz/bert-base-turkish-cased with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dbmdz/bert-base-turkish-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dbmdz/bert-base-turkish-cased: direct link, hf CLI and curl.
- Browser
- Download file 445 MB
-
https://huggingface.co/dbmdz/bert-base-turkish-cased/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dbmdz/bert-base-turkish-cased/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dbmdz/bert-base-turkish-cased/resolve/main/pytorch_model.bin
445 MB
- Xet hash:
- db1d768b068622749f57e3318d41a2c6aa5e4193f5ded079321e8f92e5248abf
- Size of remote file:
- 445 MB
- SHA256:
- 881c43cedf293003e7c25917a085bb1ef1d96a2c95dbb305a2172b512ef71ac8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.