Model Details
Full Model IDdistilbert/distilbert-base-uncased-finetuned-sst-2-english
Pipeline / Tasktext-classification
Librarytransformers
Downloads (all-time)3.6M
Likes910
Last Modified12/19/2023
Author / Orgdistilbert
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="distilbert/distilbert-base-uncased-finetuned-sst-2-english")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchtfrustonnxsafetensorsdistilberttext-classificationendataset:sst2dataset:gluearxiv:1910.01108doi:10.57967/hf/0181license:apache-2.0model-indexendpoints_compatibledeploy:azureregion:us
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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
⬇ Downloads3.6M
❤️ Community Likes910
🛠️ 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.