Instructions to use psxjp5/mt5-small_large_lr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use psxjp5/mt5-small_large_lr with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("psxjp5/mt5-small_large_lr") model = AutoModelForSeq2SeqLM.from_pretrained("psxjp5/mt5-small_large_lr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from psxjp5/mt5-small_large_lr: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/psxjp5/mt5-small_large_lr/resolve/main/training_args.bin
- Command line
-
hf download hf://psxjp5/mt5-small_large_lr/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/psxjp5/mt5-small_large_lr/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- eb0061687763053c8b7f23ebb0e03871a9a30c356a1ba6d9e8582b2d47983fa5
- Size of remote file:
- 4.09 kB
- SHA256:
- e77b4965e6d7365466cc9c9b6211c733463bcba609b7a519ca3bd159d064a145
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