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:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("stas/mt5-tiny-random") model = AutoModelForSeq2SeqLM.from_pretrained("stas/mt5-tiny-random") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24b5099b31bec6a1b35039a94a5bc52612ea4c78e1c13668346f5f4ad95448e3
- Size of remote file:
- 3.34 MB
- SHA256:
- e47ef1ea6344ab7c8e41bb0001ff32ded49a2c17c6539994e242e30acb15fd85
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.