Instructions to use hf-internal-testing/tiny-random-MT5EncoderModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MT5EncoderModel with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MT5EncoderModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MT5EncoderModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hf-internal-testing/tiny-random-MT5EncoderModel: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-MT5EncoderModel/resolve/fedca37259e7e636d6a9a44dc826fea53515ccfe/tokenizer.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MT5EncoderModel@fedca37259e7e636d6a9a44dc826fea53515ccfe/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/hf-internal-testing/tiny-random-MT5EncoderModel/resolve/fedca37259e7e636d6a9a44dc826fea53515ccfe/tokenizer.json
16.3 MB
- Xet hash:
- 702f3e9ccc6b61dd2345d6f4dc6949f06bc99e149672816411167314819745f1
- Size of remote file:
- 16.3 MB
- SHA256:
- 87a036c0dfd2d80e1202a7e2961aeee653ff63d67cd369b155c78a6e2003a390
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