Instructions to use kmok1/cs_mT5-large2_2e-5_50_v0.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmok1/cs_mT5-large2_2e-5_50_v0.3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kmok1/cs_mT5-large2_2e-5_50_v0.3") model = AutoModelForSeq2SeqLM.from_pretrained("kmok1/cs_mT5-large2_2e-5_50_v0.3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be936d4f83b43f897e64c10c46647a9f86179b12b7e6f1c1e4b8b9a991d76607
- Size of remote file:
- 5.11 kB
- SHA256:
- c5dd3ad47b204db76f5ddb8d5fc9264d93b9b61b99e031f6f71f4f25b39e1cb7
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