Instructions to use yhavinga/t5-base-36L-dutch-english-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yhavinga/t5-base-36L-dutch-english-cased with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("yhavinga/t5-base-36L-dutch-english-cased") model = AutoModelForMultimodalLM.from_pretrained("yhavinga/t5-base-36L-dutch-english-cased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 535e9b96942700336e18c9572c77c8a1052ca10fbd295757ddd24ec88d02ab1c
- Size of remote file:
- 2.92 GB
- SHA256:
- ee21f551cb4b1db290ed662997639369e65ce44b108bba4577f2045e572249aa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.