Text Classification
Transformers
Safetensors
xlm-roberta
toxicity,
indian-languages,
content-moderation,
multilingual,
text-embeddings-inference
Instructions to use tsmaitry/devica-toxicity-xlmr-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tsmaitry/devica-toxicity-xlmr-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tsmaitry/devica-toxicity-xlmr-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tsmaitry/devica-toxicity-xlmr-large") model = AutoModelForSequenceClassification.from_pretrained("tsmaitry/devica-toxicity-xlmr-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33c22a2c1190522df8d5dc16159711a2392657c3d07fe23fb91f2019c584b3aa
- Size of remote file:
- 16.8 MB
- SHA256:
- 9ce77ba8b4c297b974086f177384cc0ce96d6d08158072cc9cdc0e9f16c48dea
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