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:
- cb57901b6fc322b430d249a4f5e1258586e142cb5206e1ff035ec840c2937a55
- Size of remote file:
- 4.25 MB
- SHA256:
- 3bcab6e6f65261d1395ff90a022b8710aa089c431b52e1b14bc76103a7bd9280
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.