Instructions to use multidefmod/dore-mt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use multidefmod/dore-mt5-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("multidefmod/dore-mt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("multidefmod/dore-mt5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-82420-epoch-10/pytorch_model.bin from multidefmod/dore-mt5-base: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/multidefmod/dore-mt5-base/resolve/main/checkpoint-82420-epoch-10/pytorch_model.bin
- Command line
-
hf download hf://multidefmod/dore-mt5-base/checkpoint-82420-epoch-10/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/multidefmod/dore-mt5-base/resolve/main/checkpoint-82420-epoch-10/pytorch_model.bin
2.33 GB
- Xet hash:
- 7c224b42ead9d11067f4d03b1ca0164e102b87bb17ebcbf46bb9535c18473d59
- Size of remote file:
- 2.33 GB
- SHA256:
- 55e72c7cab8165e0a23941ace240d2d0a5326be328490a5027eacc9f65bf0194
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