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:
- beb5d2c95728f5dc4c28398b383f81002a7e90c90a05d4e707f2ae8f8219393b
- Size of remote file:
- 6.47 GB
- SHA256:
- db444f8aee92d640dbb8127f23ef2dc9c11770e6fe0b31d9b9350d17f943bad3
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