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:
- 2ce43384d1ac710ebc57a5bb8f5019a43de48224a2ff6cd624b6f795cdffa47e
- Size of remote file:
- 8.45 MB
- SHA256:
- 9d6f4bf1435354b24ff197b80de38fd6f2014e2e3e6d9c3b3cdea00ff54a0141
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.