🤖 question-answering

splinter-base

tau/splinter-base

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transformers
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Model Details
Full Model IDtau/splinter-base
Pipeline / Taskquestion-answering
Librarytransformers
Downloads (all-time)129.0K
Likes1
Last Modified8/17/2021
Author / Orgtau
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="tau/splinter-base")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
transformerspytorchsplinterquestion-answeringSplinterModelenlicense:apache-2.0endpoints_compatibledeploy:azureregion:us
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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
Downloads129.0K
❤️ Community Likes1
🛠️ 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?