Transformers
PyTorch
English
Romanian
mt5
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use Lvxue/finetuned-mt5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lvxue/finetuned-mt5-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Lvxue/finetuned-mt5-base") model = AutoModelForSeq2SeqLM.from_pretrained("Lvxue/finetuned-mt5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Lvxue/finetuned-mt5-base: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/Lvxue/finetuned-mt5-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Lvxue/finetuned-mt5-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Lvxue/finetuned-mt5-base/resolve/main/pytorch_model.bin
2.33 GB
- Xet hash:
- aec69afe8380f1373816bfa4692d5b7820c6065ae036a4570989757010fb6184
- Size of remote file:
- 2.33 GB
- SHA256:
- df2ee65f360feace00a05321513ea33c2ec35797f19e5c9371858ee4486d1a64
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