Instructions to use gutierrez310/som_ml_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gutierrez310/som_ml_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="gutierrez310/som_ml_model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gutierrez310/som_ml_model") model = AutoModel.from_pretrained("gutierrez310/som_ml_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc7e922faf46da9f7fa211dd52e0af8bae933ac5aed0a174b4dd6c7376186a85
- Size of remote file:
- 17.5 MB
- SHA256:
- 01cde52fae601efd957e212d03e313f0e206995fe3b3d1081e7837089199b3a4
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