Instructions to use hf-internal-testing/tiny-random-UMT5EncoderModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UMT5EncoderModel with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-UMT5EncoderModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-UMT5EncoderModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-UMT5EncoderModel: direct link, hf CLI and curl.
- Browser
- Download file 33 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-UMT5EncoderModel/resolve/207673a27b8cd44dcb951c58c70a9ce5d171fe31/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-UMT5EncoderModel@207673a27b8cd44dcb951c58c70a9ce5d171fe31/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-UMT5EncoderModel/resolve/207673a27b8cd44dcb951c58c70a9ce5d171fe31/pytorch_model.bin
33 MB
- Xet hash:
- 21e3006e4052b905c698b18a35fa32993b9b182027c4a8319e9ea687782fade9
- Size of remote file:
- 33 MB
- SHA256:
- 388021d774eca0469a727fbbb7cdb6d55983d893dd05a1470c7429be036d3d74
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