Model Details
Full Model IDARTeLab/mbart-summarization-fanpage
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)40.8K
Likes0
Last Modified9/12/2023
Author / OrgARTeLab
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="ARTeLab/mbart-summarization-fanpage")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchsafetensorsmbarttext2text-generationsummarizationitdataset:ARTeLab/fanpagebase_model:facebook/mbart-large-cc25base_model:finetune:facebook/mbart-large-cc25endpoints_compatibleregion:us
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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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⬇ Downloads40.8K
❤️ Community Likes0
🛠️ 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.