Model Details
Full Model IDlxyuan/distilbert-base-multilingual-cased-sentiments-student
Pipeline / Tasktext-classification
Librarytransformers
Downloads (all-time)708.0K
Likes312
Last Modified3/3/2025
Author / Orglxyuan
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="lxyuan/distilbert-base-multilingual-cased-sentiments-student")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
transformerspytorchonnxsafetensorsdistilberttext-classificationsentiment-analysiszero-shot-distillationdistillationzero-shot-classificationdebarta-v3enardeesfrjazhidhiitmsptdataset:tyqiangz/multilingual-sentimentsdoi:10.57967/hf/1422license:apache-2.0text-embeddings-inferenceendpoints_compatibleregion:us
More Text Classification Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
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
⬇ Downloads708.0K
����� Community Likes312
🛠�� 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.