Text Classification
Transformers
Safetensors
English
Urdu
xlm-roberta
emotion-detection
multilingual
roman-urdu
code-mixed
pakistan
accuracy
f1
text-embeddings-inference
Instructions to use muhammadsuleman1533/xlm-roberta-multilingual-emotion-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muhammadsuleman1533/xlm-roberta-multilingual-emotion-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="muhammadsuleman1533/xlm-roberta-multilingual-emotion-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("muhammadsuleman1533/xlm-roberta-multilingual-emotion-classifier") model = AutoModelForSequenceClassification.from_pretrained("muhammadsuleman1533/xlm-roberta-multilingual-emotion-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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