Instructions to use edharepe/T5_generacion_titulos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edharepe/T5_generacion_titulos with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("edharepe/T5_generacion_titulos") model = AutoModelForSeq2SeqLM.from_pretrained("edharepe/T5_generacion_titulos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a0ea72dffe9d54300b8a03780b5f1ab9a8ed09ff346990b0e5c133c299b5ff0
- Size of remote file:
- 892 MB
- SHA256:
- beac0f0d3e87dddf88ee0e7810abff043d6b4d64d4783444d59473f9887c13e3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.