Instructions to use GroNLP/T0pp-sharded with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GroNLP/T0pp-sharded with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("GroNLP/T0pp-sharded") model = AutoModelForMultimodalLM.from_pretrained("GroNLP/T0pp-sharded") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ea29c384a5123db3813e23cd4608427559a7e27432a5ea816f3c47c564a558b
- Size of remote file:
- 940 MB
- SHA256:
- 4b4cca5c92c479ea93347d1c812d2ea2a87516051335c43a464db45c3a1d766c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.