Instructions to use Gowreesh234/flan-t5-base-finetuned-dialougesum-en-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gowreesh234/flan-t5-base-finetuned-dialougesum-en-es with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Gowreesh234/flan-t5-base-finetuned-dialougesum-en-es") model = AutoModelForSeq2SeqLM.from_pretrained("Gowreesh234/flan-t5-base-finetuned-dialougesum-en-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24dad66f2a4ae5abe4ff39eab7d8005fe559318a9a3743eeb1b0653fbf001cd7
- Size of remote file:
- 495 MB
- SHA256:
- 84a136a9c7d95998b7ff6d206117d705b0e503334750db0e748797792cd0f329
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.