Instructions to use hf-internal-testing/tiny-random-T5EncoderModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-T5EncoderModel with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-T5EncoderModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-T5EncoderModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 839ef7b5c304c19b59b6a7c3c27b08219a782d513af2fec09cd321bfad77f986
- Size of remote file:
- 4.25 MB
- SHA256:
- db056c51fd0e857161c241755716bb479a8db1c8616bd48137361f40fd4167ae
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.