Instructions to use baobuiquang/FE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baobuiquang/FE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="baobuiquang/FE")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("baobuiquang/FE") model = AutoModel.from_pretrained("baobuiquang/FE") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81d63204a496678121b465cb8323ee875d6c0b54230f5281edd6a8607030b925
- Size of remote file:
- 1.11 GB
- SHA256:
- f061cb7641880f52895cbacab7c4ab39b0844e2e6b73794f2798de460d9fa418
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