Instructions to use kmok1/cs_mT5-large2_2e-5_50_v0.1 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_v0.1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kmok1/cs_mT5-large2_2e-5_50_v0.1") model = AutoModelForSeq2SeqLM.from_pretrained("kmok1/cs_mT5-large2_2e-5_50_v0.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3168106515af60c40265725f7dbcbd847816f6692059405612c665c415d5780
- Size of remote file:
- 5.11 kB
- SHA256:
- a6fbd8be223c2c52971414f01ec9460d3aa88e0f7b7f5694f6b58b6d3098a73a
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