Text Classification
Transformers
PyTorch
Safetensors
Marathi
English
multilingual
xlm-roberta
codemix
text-embeddings-inference
Instructions to use l3cube-pune/me-hate-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/me-hate-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="l3cube-pune/me-hate-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/me-hate-roberta") model = AutoModelForSequenceClassification.from_pretrained("l3cube-pune/me-hate-roberta") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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- model.safetensors +3 -0
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