�� Summarization

FRED-T5-Summarizer

RussianNLP/FRED-T5-Summarizer

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19.1K
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28
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Tags
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transformers
Library
Model Details
Full Model IDRussianNLP/FRED-T5-Summarizer
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)19.1K
Likes28
Last Modified4/22/2024
Author / OrgRussianNLP
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="RussianNLP/FRED-T5-Summarizer")

# Run inference
result = pipe("Your input here")
print(result)
����� Tags
transformerssafetensorst5text2text-generationsummarizationrulicense:mittext-generation-inferenceendpoints_compatibleregion: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: Summarization

This model is designed for the Summarization task. Explore more models for this use case.

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📊 Popularity
Downloads19.1K
����� Community Likes28
🛠�� 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?