Instructions to use ChillingDream/dap-mbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChillingDream/dap-mbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ChillingDream/dap-mbert-base")# Load model directly from transformers import AutoTokenizer, BertForRLM tokenizer = AutoTokenizer.from_pretrained("ChillingDream/dap-mbert-base") model = BertForRLM.from_pretrained("ChillingDream/dap-mbert-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc206ffa0e7bd5e34f3eca7110654988556da324fe883d5684aa2296b9ee6d5e
- Size of remote file:
- 711 MB
- SHA256:
- b0f2a1a886f7a4850bff53d60481351e838a38fd13c37fa37fe17caeddf1f1af
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