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 training_args.bin from bgk/berteng: direct link, hf CLI and curl.
- Browser
- Download file 3.26 kB
-
https://huggingface.co/bgk/berteng/resolve/main/training_args.bin
- Command line
-
hf download hf://bgk/berteng/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/bgk/berteng/resolve/main/training_args.bin
3.26 kB
- Xet hash:
- 6f61477d5e0042d432b24f1f75248f5b52278e927a18bb83f65f111c1401b943
- Size of remote file:
- 3.26 kB
- SHA256:
- d85b5e7e5c2e89e7a472fae83f7015dea02ebd7d9760753b443cdaf7accc1705
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