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 pytorch_model.bin from stas/mt5-tiny-random: direct link, hf CLI and curl.
- Browser
- Download file 3.34 MB
-
https://huggingface.co/stas/mt5-tiny-random/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://stas/mt5-tiny-random/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stas/mt5-tiny-random/resolve/main/pytorch_model.bin
3.34 MB
- Xet hash:
- 24b5099b31bec6a1b35039a94a5bc52612ea4c78e1c13668346f5f4ad95448e3
- Size of remote file:
- 3.34 MB
- SHA256:
- e47ef1ea6344ab7c8e41bb0001ff32ded49a2c17c6539994e242e30acb15fd85
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