Instructions to use sign/utf32-lm-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sign/utf32-lm-tiny with Transformers:
# Load model directly from transformers import CharacterCausalLMWrapper model = CharacterCausalLMWrapper.from_pretrained("sign/utf32-lm-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cb975da55d710a8f90ae5f2eac44059c75c11adfb4a03919ec2285165cf7c41
- Size of remote file:
- 25 MB
- SHA256:
- c9c02aa1d0972610f5fe2f3845c15451b08bc0d41ca4e8bfd06eae04daf61f04
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