Model Details
Full Model IDdeepset/roberta-base-squad2
Pipeline / Taskquestion-answering
Librarytransformers
Downloads (all-time)512.2K
Likes946
Last Modified9/24/2024
Author / Orgdeepset
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("question-answering", model="deepset/roberta-base-squad2")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchtfjaxrustsafetensorsrobertaquestion-answeringendataset:squad_v2base_model:FacebookAI/roberta-basebase_model:finetune:FacebookAI/roberta-baselicense:cc-by-4.0model-indexendpoints_compatibledeploy:azureregion:us
More question-answering 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: question-answering
This model is designed for the question-answering task. Explore more models for this use case.
All question-answering Models →📊 Popularity
⬇ Downloads512.2K
❤️ Community Likes946
🛠️ 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.