Instructions to use FPTAI/vibert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FPTAI/vibert-base-cased with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FPTAI/vibert-base-cased", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab12a5205b1fbcb04b256289794a7e2721f92b328d634b5268375e686a86b6ce
- Size of remote file:
- 461 MB
- SHA256:
- 4f96f440f2081ea22fe9565f477a847f706f5d5e59a232ecb5f9287939e55763
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