Transformers
PyTorch
TensorFlow
ONNX
Safetensors
English
t5
text2text-generation
summary
summarizer
Eval Results (legacy)
text-generation-inference
Instructions to use shorecode/t5-efficient-tiny-summarizer-general-purpose-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shorecode/t5-efficient-tiny-summarizer-general-purpose-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("shorecode/t5-efficient-tiny-summarizer-general-purpose-v2") model = AutoModelForSeq2SeqLM.from_pretrained("shorecode/t5-efficient-tiny-summarizer-general-purpose-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- summary
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- summarizer
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widget:
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---
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- summary
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- summarizer
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widget:
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- text: Model training
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output:
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url: Screenshot_20251030_222933.png
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metrics:
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- f1
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- rouge
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model-index:
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- name: t5-efficient-tiny-summarizer-general-purpose-v2
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results:
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- task:
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type: Summarization
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dataset:
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name: shorecode/summary-collection-60k-rows
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type: shorecode/summary-collection-60k-rows
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metrics:
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- name: f1 Score
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type: f1 Score
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value: 0.295
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---
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