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 flax_model.msgpack 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/flax_model.msgpack
- Command line
-
hf download hf://cardiffnlp/bertweet-base-offensive/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/cardiffnlp/bertweet-base-offensive/resolve/main/flax_model.msgpack
540 MB
- Xet hash:
- 70b5c53954f247564bc3d236560290071732397ae12593588c22704e28c7e95a
- Size of remote file:
- 540 MB
- SHA256:
- fb03f44aecda4f590dc602378a52bc199cb630dca0a71afa00fc03f1b9e4b516
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