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:
- c1ea2f935c659abb264fee75e48bf7623f0767984ad40a9d21ae423e4d732d3e
- Size of remote file:
- 8.45 MB
- SHA256:
- c0c797c4ceaec32e7e35ebb6ceff5245e933d4a246320a43492e114f2adf4c30
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.