Transformers
PyTorch
Safetensors
English
t5
text2text-generation
text2text generation
text-generation-inference
Instructions to use haining/scientific_abstract_simplification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use haining/scientific_abstract_simplification with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("haining/scientific_abstract_simplification") model = AutoModelForSeq2SeqLM.from_pretrained("haining/scientific_abstract_simplification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# TL;DR
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Scientific Abstract Simplification rewrites hard-to-read scientific abstracts😵 into
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If you already used our baseline model [`sas_baseline`](https://huggingface.co/haining/sas_baseline), the current model just performs better on **all** evaluation metrics.
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Try it now with the Hosted inference API on the right.
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# TL;DR
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Scientific Abstract Simplification rewrites hard-to-read scientific abstracts😵 into simpler yet relevant scientific stories😇. We hope our model can make scientific knowledge accessible for everyone🤗.
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If you already used our baseline model [`sas_baseline`](https://huggingface.co/haining/sas_baseline), the current model just performs better on **all** evaluation metrics.
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Try it now with the Hosted inference API on the right.
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