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
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#This model was built to shorten text to be injected into LLM prompts to reduce API calling costs!
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#Very high compression (7x) meaning the text is 7 times smaller when sent to your LLM provider!
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# This model was built to shorten text to be injected into LLM prompts to reduce API calling costs!
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# Very high compression (7x) meaning the text is 7 times smaller when sent to your LLM provider!
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