Instructions to use pucpr/eHelpBERTpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pucpr/eHelpBERTpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pucpr/eHelpBERTpt")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pucpr/eHelpBERTpt") model = AutoModelForTokenClassification.from_pretrained("pucpr/eHelpBERTpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from pucpr/eHelpBERTpt: direct link, hf CLI and curl.
- Browser
- Download file 710 MB
-
https://huggingface.co/pucpr/eHelpBERTpt/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://pucpr/eHelpBERTpt/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pucpr/eHelpBERTpt/resolve/main/pytorch_model.bin
710 MB
- Xet hash:
- 853640af879e52bf24e1aa08fd2d8ec0262af8b7ecf8d2fd2d14285344f608df
- Size of remote file:
- 710 MB
- SHA256:
- 89f215f9467ecb04dfbd27d2dfb770f5c02871a6304d34d1c2d022e9aa2406ec
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