Model Details
Full Model IDknkarthick/MEETING_SUMMARY
Pipeline / Tasksummarization
Librarytransformers
Downloads (all-time)43.5K
Likes196
Last Modified3/27/2023
Author / Orgknkarthick
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="knkarthick/MEETING_SUMMARY")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
transformerspytorchtfsafetensorsbarttext2text-generationseq2seqsummarizationenlicense:apache-2.0model-indexendpoints_compatibledeploy:azureregion: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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⬇ Downloads43.5K
����� Community Likes196
🛠�� 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.