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
- Xet hash:
- 15310cd11613546b1dd0b34a2ba7145380390259ba306366c12b71bc838d8428
- Size of remote file:
- 3.13 GB
- SHA256:
- 0fdb01cfe98596c1a13a78ded6f74d1dc1de63b4705c8878fb6c6cf95039c02f
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