Transformers
PyTorch
ONNX
Safetensors
English
t5
text2text-generation
summary
summarizer
Eval Results (legacy)
text-generation-inference
Instructions to use shorecode/t5-efficient-tiny-summarizer-general-purpose-v3 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-v3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("shorecode/t5-efficient-tiny-summarizer-general-purpose-v3") model = AutoModelForSeq2SeqLM.from_pretrained("shorecode/t5-efficient-tiny-summarizer-general-purpose-v3") - Notebooks
- Google Colab
- Kaggle
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README.md
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# This model was built to shorten text that is injected into LLM prompts to reduce API calling costs
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https://api.wandb.ai/links/shorecode-shorecode-llc/6udfudmr
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# This model was built to shorten text that is 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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https://api.wandb.ai/links/shorecode-shorecode-llc/6udfudmr
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