🤖 question-answering

mdeberta-v3-base-squad2

timpal0l/mdeberta-v3-base-squad2

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transformers
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Model Details
Full Model IDtimpal0l/mdeberta-v3-base-squad2
Pipeline / Taskquestion-answering
Librarytransformers
Downloads (all-time)288.4K
Likes259
Last Modified11/26/2024
Author / Orgtimpal0l
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="timpal0l/mdeberta-v3-base-squad2")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
transformerspytorchsafetensorsdeberta-v2question-answeringdebertadeberta-v3mdebertaqamultilingualafamarasazbebgbnbrbscacscydadeeleneoeset
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🚀 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
Downloads288.4K
❤️ Community Likes259
🛠️ 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.
👋 Need help with code?