Instructions to use cardiffnlp/twitter-roberta-base-offensive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/twitter-roberta-base-offensive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/twitter-roberta-base-offensive")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-offensive") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-offensive", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from cardiffnlp/twitter-roberta-base-offensive: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/cardiffnlp/twitter-roberta-base-offensive/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://cardiffnlp/twitter-roberta-base-offensive/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/cardiffnlp/twitter-roberta-base-offensive/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- f2e3ba666367c8f7b17e2cf4dd138b87c3f1f169476bef7f2343dce8d1bca762
- Size of remote file:
- 499 MB
- SHA256:
- 80324baf0389b06bd5ec24f98e2cb4ac39a90ac22dc42a7244c8fd4f156ab77b
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