Instructions to use buerokratt/bert-truecaser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use buerokratt/bert-truecaser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="buerokratt/bert-truecaser")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("buerokratt/bert-truecaser") model = AutoModelForTokenClassification.from_pretrained("buerokratt/bert-truecaser", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from buerokratt/bert-truecaser: direct link, hf CLI and curl.
- Browser
- Download file 991 MB
-
https://huggingface.co/buerokratt/bert-truecaser/resolve/main/optimizer.pt
- Command line
-
hf download hf://buerokratt/bert-truecaser/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/buerokratt/bert-truecaser/resolve/main/optimizer.pt
991 MB
- Xet hash:
- f0f97007f52e411f11287007147ff0612b988e43d86c3f8b83b5d919d7f4360a
- Size of remote file:
- 991 MB
- SHA256:
- 26fe735299ac83670492b5c17a315079cb3a8bf525b2173e0fdb4cb31f301e02
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