Model Details
Full Model IDdeepset/tinyroberta-squad2
Pipeline / Taskquestion-answering
Librarytransformers
Downloads (all-time)142.2K
Likes114
Last Modified9/26/2024
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/tinyroberta-squad2")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchsafetensorsrobertaquestion-answeringendataset:squad_v2arxiv:1909.10351license:cc-by-4.0model-indexendpoints_compatibledeploy:azureregion:us
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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
⬇ Downloads142.2K
❤️ Community Likes114
🛠️ 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.