Instructions to use tum-nlp/bert-hateXplain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tum-nlp/bert-hateXplain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tum-nlp/bert-hateXplain")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tum-nlp/bert-hateXplain") model = AutoModelForSequenceClassification.from_pretrained("tum-nlp/bert-hateXplain", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from tum-nlp/bert-hateXplain: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/tum-nlp/bert-hateXplain/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://tum-nlp/bert-hateXplain@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/tum-nlp/bert-hateXplain/resolve/refs%2Fpr%2F2/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.