Summarization
Transformers
TensorBoard
Safetensors
English
t5
text2text-generation
summarizer
text summarization
abstractive summarization
text-generation-inference
Instructions to use KipperDev/t5_summarizer_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KipperDev/t5_summarizer_model with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="KipperDev/t5_summarizer_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KipperDev/t5_summarizer_model") model = AutoModelForSeq2SeqLM.from_pretrained("KipperDev/t5_summarizer_model") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- summarizer
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- text summarization
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- abstractive summarization
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---
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[](https://shields.io/)
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# Authors
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This model card was written by [Fernanda Kipper](https://www.fernandakipper.com/)
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- summarizer
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- text summarization
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pipeline_tag: summarization
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---
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[](https://shields.io/)
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# Authors
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This model card was written by [Fernanda Kipper](https://www.fernandakipper.com/)
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