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:
- d3815103f70dafa5305321874aae2e3a5c9afbeb208a4358bbb21fdec6adf0ba
- Size of remote file:
- 4.25 MB
- SHA256:
- 268953fe06bf741e8dd1e3e50a0bc72d9ad3d0916c65eb45d41a3b71a2c23386
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.