Model Details
Full Model IDIlyaGusev/rut5_base_sum_gazeta
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)11.8K
Likes18
Last Modified7/13/2022
Author / OrgIlyaGusev
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("summarization", model="IlyaGusev/rut5_base_sum_gazeta")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorcht5text2text-generationsummarizationrudataset:IlyaGusev/gazetalicense:apache-2.0text-generation-inferenceendpoints_compatibledeploy:azureregion:us
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Open on Hugging Face →Browse Model Files ↗← Browse All Models📝 Task: Summarization
This model is designed for the Summarization task. Explore more models for this use case.
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⬇ Downloads11.8K
❤️ Community Likes18
🛠️ 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.