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:
# pip install -U transformers accelerate # 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
Download tokenizer.json from haining/scientific_abstract_simplification: direct link, hf CLI and curl.
- Browser
- Download file 2.42 MB
-
https://huggingface.co/haining/scientific_abstract_simplification/resolve/main/tokenizer.json
- Command line
-
hf download hf://haining/scientific_abstract_simplification/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/haining/scientific_abstract_simplification/resolve/main/tokenizer.json
2.42 MB
File too large to display, you can check the raw version instead.