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/5cd9b6ecac7fa84b619ff53142960ef131288f73/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-UMT5EncoderModel@5cd9b6ecac7fa84b619ff53142960ef131288f73/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-UMT5EncoderModel/resolve/5cd9b6ecac7fa84b619ff53142960ef131288f73/pytorch_model.bin
33 MB
- Xet hash:
- e29af0cd70def0db0afed77ef0a0f51e6a8104ed5e1ab4256024b2e7f2fee696
- Size of remote file:
- 33 MB
- SHA256:
- 6eaf2e2414fa09845f9619ba7d226fbe228f22c2a66638017471244044a90386
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