Instructions to use stas/mt5-tiny-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stas/mt5-tiny-random with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("stas/mt5-tiny-random") model = AutoModelForSeq2SeqLM.from_pretrained("stas/mt5-tiny-random", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from stas/mt5-tiny-random: direct link, hf CLI and curl.
- Browser
- Download file 6.56 MB
-
https://huggingface.co/stas/mt5-tiny-random/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://stas/mt5-tiny-random@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/stas/mt5-tiny-random/resolve/refs%2Fpr%2F1/flax_model.msgpack
6.56 MB
- Xet hash:
- 4739fd78a08deb2fa5ca06bd68fd32450818e976aff4bf57883710101e2dab38
- Size of remote file:
- 6.56 MB
- SHA256:
- ecfb8775360dc89346a072c29152eb8fba4d20068a11ec08305fb0a73e6be2ff
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