Transformers
Safetensors
t5
text2text-generation
simplification
Generated from Trainer
text-generation-inference
Instructions to use CarlosAraEspinosa/summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CarlosAraEspinosa/summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CarlosAraEspinosa/summarization") model = AutoModelForSeq2SeqLM.from_pretrained("CarlosAraEspinosa/summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 491884e99cb7f88c3da952a44cda5acdde44e272749f95ff9aed2617154132a1
- Size of remote file:
- 5.33 kB
- SHA256:
- 9c309e87400b70ae400a9bd6ba43a643fe9f38881463b641b1fa4662e051009a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.