Instructions to use LendeaViva/bert-large-punloc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LendeaViva/bert-large-punloc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="LendeaViva/bert-large-punloc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("LendeaViva/bert-large-punloc") model = AutoModelForTokenClassification.from_pretrained("LendeaViva/bert-large-punloc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from LendeaViva/bert-large-punloc: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/LendeaViva/bert-large-punloc/resolve/main/training_args.bin
- Command line
-
hf download hf://LendeaViva/bert-large-punloc/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/LendeaViva/bert-large-punloc/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 58f845618df785dad3e381d9a8fb9c2fe1addef6f29f8d7a5ffe80b7b494c772
- Size of remote file:
- 4.92 kB
- SHA256:
- a5f2216941b63186e8e638607dc19af80e48c6c2ead7919e7e47d63278d9b7fe
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