Instructions to use vikenkd/mt5-base-medium-poem-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vikenkd/mt5-base-medium-poem-generation with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vikenkd/mt5-base-medium-poem-generation") model = AutoModelForSeq2SeqLM.from_pretrained("vikenkd/mt5-base-medium-poem-generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 806f87e6fe769e74b096c8a206956ef2a43cecb512456cead588edfb1592a944
- Size of remote file:
- 16.4 MB
- SHA256:
- 2bc772e813ad3cac08b9094f86da51e51099a5972b4618474a72784f06eef279
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