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
Add pipeline tag, library name, link to paper
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by nielsr HF Staff - opened
README.md
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license: mit
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license: mit
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library_name: transformers
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pipeline_tag: feature-extraction
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This repository contains the model of the paper [Dual-Alignment Pre-training for Cross-lingual Sentence Embedding](https://huggingface.co/papers/2305.09148).
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