Instructions to use jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01") model = AutoModelForSeq2SeqLM.from_pretrained("jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01/resolve/6c2348a0ed7d6faf30eb720ae69cb0f8f7dc9748/training_args.bin
- Command line
-
hf download hf://jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01@6c2348a0ed7d6faf30eb720ae69cb0f8f7dc9748/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01/resolve/6c2348a0ed7d6faf30eb720ae69cb0f8f7dc9748/training_args.bin
4.22 kB
- Xet hash:
- aeda19e4a141271b274858e9baa85123a988c600bbda4ce3be9dfe2356bf2e53
- Size of remote file:
- 4.22 kB
- SHA256:
- 6fcdbdb6271ce500943fc80093aacca30a7a1e385ccf41be0fba1182d4f87fb7
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