Instructions to use ashabrawy/lev_aligned_msa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashabrawy/lev_aligned_msa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ashabrawy/lev_aligned_msa")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ashabrawy/lev_aligned_msa") model = AutoModel.from_pretrained("ashabrawy/lev_aligned_msa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e87499eba0eeca331250a3ae7038565e02b81cf35eecf1341d0b51860535627b
- Size of remote file:
- 436 MB
- SHA256:
- 866815c902ab19166d2f04c29ac1e87a8900f9725f244bfa27d3b0684d3582f9
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