Text Classification
Transformers
ONNX
xlm-roberta
toxicity
toxic detection
text-embeddings-inference
Instructions to use hoan/multilingual-toxic-xlm-roberta-dynamic-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hoan/multilingual-toxic-xlm-roberta-dynamic-quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hoan/multilingual-toxic-xlm-roberta-dynamic-quantized")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hoan/multilingual-toxic-xlm-roberta-dynamic-quantized") model = AutoModelForSequenceClassification.from_pretrained("hoan/multilingual-toxic-xlm-roberta-dynamic-quantized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aea4c283df0ba1b545b5899fd0b257def695c1c57052cdeb76589721d4cf3a8b
- Size of remote file:
- 17.1 MB
- SHA256:
- 15c2549547974954d493ed56303f1f82e6708d261b9b0533d224938102892f38
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