Instructions to use MattZid/xlm-roberta-base-hate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MattZid/xlm-roberta-base-hate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MattZid/xlm-roberta-base-hate")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MattZid/xlm-roberta-base-hate") model = AutoModelForSequenceClassification.from_pretrained("MattZid/xlm-roberta-base-hate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from MattZid/xlm-roberta-base-hate: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/MattZid/xlm-roberta-base-hate/resolve/main/tokenizer.json
- Command line
-
hf download hf://MattZid/xlm-roberta-base-hate/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/MattZid/xlm-roberta-base-hate/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- f9b4813968d48faa32a02251f368ef957640c0bed80404c10915134e6adf9924
- Size of remote file:
- 17.1 MB
- SHA256:
- d6f76fe13d42f80dcee0cb86a1aeb5f14f8909bb8a8782f7a4a4ad76697ef164
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