Instructions to use ugiugi/twitter-t5-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ugiugi/twitter-t5-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ugiugi/twitter-t5-mlm")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ugiugi/twitter-t5-mlm") model = AutoModel.from_pretrained("ugiugi/twitter-t5-mlm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ab6d75faa4e182731b7d0792361a9e48413daf485428346bce59ae6e467bf83
- Size of remote file:
- 990 MB
- SHA256:
- 273a754910c4bc2cd3a6a4903cf258facd7cfcbf79be705346212d2908492217
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