Instructions to use cardiffnlp/twitter-roberta-base-hate-latest-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/twitter-roberta-base-hate-latest-st with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/twitter-roberta-base-hate-latest-st")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-hate-latest-st") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-hate-latest-st", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from cardiffnlp/twitter-roberta-base-hate-latest-st: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/cardiffnlp/twitter-roberta-base-hate-latest-st/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://cardiffnlp/twitter-roberta-base-hate-latest-st/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cardiffnlp/twitter-roberta-base-hate-latest-st/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- df563e2472c8d9f64bc0cd0d2f06231ba4cbc0a4cc01da2aa22ff322f61b450f
- Size of remote file:
- 499 MB
- SHA256:
- a2b13928d9718d7d68e82588b46a9fd0f3ef5b839bcfe4f630cb15733ce4d2ed
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