Instructions to use mlnotes/tape with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlnotes/tape with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mlnotes/tape")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mlnotes/tape") model = AutoModel.from_pretrained("mlnotes/tape") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 769196bf7130fcfe20b5ca6fffeea7e666911ce0840d21fc27b02eb60cb0852f
- Size of remote file:
- 370 MB
- SHA256:
- 7cf24153b002ea4dedc60f87649cbb4997d4273cb05a6d7acbefa696c1cd4d34
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