Model Details
Full Model IDjoeddav/bart-large-mnli-yahoo-answers
Pipeline / Taskzero-shot-classification
Librarytransformers
Downloads (all-time)66.2K
Likes13
Last Modified9/15/2025
Author / Orgjoeddav
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("zero-shot-classification", model="joeddav/bart-large-mnli-yahoo-answers")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchjaxsafetensorsbarttext-classificationzero-shot-classificationendataset:yahoo-answersarxiv:1909.00161base_model:facebook/bart-large-mnlibase_model:finetune:facebook/bart-large-mnlidoi:10.57967/hf/6543license:apache-2.0endpoints_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: zero-shot-classification
This model is designed for the zero-shot-classification task. Explore more models for this use case.
All zero-shot-classification Models →📊 Popularity
⬇ Downloads66.2K
❤️ Community Likes13
🛠️ 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.