Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use darelphilip/hinglish-toxicity-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use darelphilip/hinglish-toxicity-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="darelphilip/hinglish-toxicity-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("darelphilip/hinglish-toxicity-roberta") model = AutoModelForSequenceClassification.from_pretrained("darelphilip/hinglish-toxicity-roberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97d9f8cac215d483a41d1c0b993ce88fdc3c20ee450007531e6bcba569214ead
- Size of remote file:
- 5.2 kB
- SHA256:
- 2afca1233982e1a0666c8a325caa09427681e72495a94f078333423e7d68932d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.