Instructions to use cardiffnlp/bertweet-base-offensive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/bertweet-base-offensive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/bertweet-base-offensive")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/bertweet-base-offensive") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/bertweet-base-offensive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from cardiffnlp/bertweet-base-offensive: direct link, hf CLI and curl.
- Browser
- Download file 540 MB
-
https://huggingface.co/cardiffnlp/bertweet-base-offensive/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://cardiffnlp/bertweet-base-offensive/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cardiffnlp/bertweet-base-offensive/resolve/main/pytorch_model.bin
540 MB
- Xet hash:
- e2e865a6262ab458c760a5ec41a2225c07ee6f856400308105acfc3b1dbd9537
- Size of remote file:
- 540 MB
- SHA256:
- e34f994b6b4083582652b8258d5c92f7e8a38a67fef31af5512e489e6fd19fc0
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