Model Details
Full Model IDSamLowe/roberta-base-go_emotions
Pipeline / Tasktext-classification
Librarytransformers
Downloads (all-time)807.3K
Likes674
Last Modified5/13/2026
Author / OrgSamLowe
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="SamLowe/roberta-base-go_emotions")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
transformerspytorchsafetensorsrobertatext-classificationemotionsmulti-class-classificationmulti-label-classificationendataset:go_emotionsdoi:10.57967/hf/3548license:mittext-embeddings-inferenceendpoints_compatibledeploy:azureregion:us
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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.
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⬇ Downloads807.3K
����� Community Likes674
🛠�� 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.