Instructions to use robvanderg/bert-base-multilingual-cased-segment1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use robvanderg/bert-base-multilingual-cased-segment1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="robvanderg/bert-base-multilingual-cased-segment1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("robvanderg/bert-base-multilingual-cased-segment1") model = AutoModel.from_pretrained("robvanderg/bert-base-multilingual-cased-segment1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a78e2b38dfcc7b136efe6ac87b2fe6242a36d59933c2596583a7811f348e563
- Size of remote file:
- 711 MB
- SHA256:
- f3032c49dc312059d563c4e13a0f762d2011846664b2309ae1c12dd8f690797c
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