Instructions to use bgk/berteng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bgk/berteng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bgk/berteng")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bgk/berteng") model = AutoModelForTokenClassification.from_pretrained("bgk/berteng", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bgk/berteng: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/bgk/berteng/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bgk/berteng/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bgk/berteng/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- 36ddd52fd00f4ace4faca618c172d36d6f47a0ccd9c24e71ceb761f1efb88cfd
- Size of remote file:
- 496 MB
- SHA256:
- debea87560cb635a7d7b2ba32c2670f65baa6ac51fafd6e6fb910d065e6e47f3
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