Instructions to use reeddg/T5sumxx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reeddg/T5sumxx with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("reeddg/T5sumxx") model = AutoModelForSeq2SeqLM.from_pretrained("reeddg/T5sumxx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1173206dcbb8a66bd38554f428b4bc655343c32200f9c0bc68d9e0a2115e1135
- Size of remote file:
- 9.96 GB
- SHA256:
- be87bfd591b5671d26f4a1d8455961700ede0d92d4f4b5d3eec8297558db99b4
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