Model Details
Full Model IDtasksource/ModernBERT-base-nli
Pipeline / Taskzero-shot-classification
Librarytransformers
Downloads (all-time)48.3K
Likes37
Last Modified1/6/2025
Author / Orgtasksource
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="tasksource/ModernBERT-base-nli")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsmodernberttext-classificationinstructnatural-language-inferencenlimnlizero-shot-classificationendataset:nyu-mll/gluedataset:facebook/anlibase_model:answerdotai/ModernBERT-basebase_model:finetune:answerdotai/ModernBERT-baselicense: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
⬇ Downloads48.3K
❤️ Community Likes37
🛠️ 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.