Feature Extraction
Transformers
Safetensors
English
bert
tadse
sentence-embeddings
contrastive-learning
model-merge
text-embeddings-inference
Instructions to use minsik-oh/template-dialogue-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minsik-oh/template-dialogue-embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="minsik-oh/template-dialogue-embedding")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("minsik-oh/template-dialogue-embedding") model = AutoModel.from_pretrained("minsik-oh/template-dialogue-embedding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
2 days ago
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Update README.md
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3 days ago
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Add the ACL 2026 paper citation
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Prepare dialogue model and dataset for public release
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Name the release for dialogue representation learning
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Present the release clearly while retaining reproducibility details
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Release the verified top2 BERT merge for private review
Verified signatureReplace the previous single-checkpoint candidate with the fixed 50/50 exported-model merge. Constraint: Keep the repository private Tested: Identical serialization tensors and probe outputs; recovered five-dataset evaluation5b89038
6 days ago
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Preserve the verified TaDSE trained-head reproduction for private review
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initial commit
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