Model Details
Full Model IDtabularisai/multilingual-sentiment-analysis
Pipeline / Tasktext-classification
Librarytransformers
Downloads (all-time)767.8K
Likes365
Last Modified4/14/2026
Author / Orgtabularisai
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-classification", model="tabularisai/multilingual-sentiment-analysis")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsdistilberttext-classificationsentiment-analysissentimentsynthetic datamulti-classsocial-media-analysiscustomer-feedbackproduct-reviewsbrand-monitoringmultilingual🇪🇺region:eusyntheticenzheshiarbnptrujademsteviko
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Open on Hugging Face →Browse Model Files ↗← Browse All Models🏷️ Task: Text Classification
This model is designed for the Text Classification task. Explore more models for this use case.
All Text Classification Models →📊 Popularity
⬇ Downloads767.8K
❤️ Community Likes365
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.