Text Classification
Transformers
Safetensors
Urdu
multilingual
xlm-roberta
urdu
roman-urdu
sentiment-analysis
sentiment-classification
social-media
text-embeddings-inference
Instructions to use yahyaqarni/socialsense-xlm-r with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yahyaqarni/socialsense-xlm-r with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yahyaqarni/socialsense-xlm-r")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yahyaqarni/socialsense-xlm-r") model = AutoModelForSequenceClassification.from_pretrained("yahyaqarni/socialsense-xlm-r") - Notebooks
- Google Colab
- Kaggle
socialsense-xmlr
Fine-tuned XLM-R for Urdu & Roman Urdu text sentiment classification.
Labels
- 0: NEGATIVE
- 1: NEUTRAL
- 2: POSITIVE
Usage
from transformers import pipeline
pipe = pipeline("text-classification",
model="yahyaqarni/socialsense-xmlr",
tokenizer="yahyaqarni/socialsense-xmlr",
top_k=None)
print(pipe("یہ بہت اچھا ہے"))
print(pipe("me bilkul khush nai hoon"))
Acknowledgements
This model was fine-tuned from cardiffnlp/twitter-xlm-roberta-base-sentiment, originally released under the Apache 2.0 License.
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