Text Classification
sentence-transformers
Safetensors
English
bert
ren
secnd
selective-classification
calibration
human-in-the-loop
text-embeddings-inference
Instructions to use Secnd-AI/ren with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Secnd-AI/ren with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Secnd-AI/ren") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Commit History
3 days ago
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Model card for the reader release
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Add meta checkpoint typed-typed-ic-ettin-400m-s6000-near-wide-fine-seed1-e8-s1-e6-s0
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Add reader checkpoint ic-ettin-400m-s6000-near-wide-fine-seed1
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5 days ago
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Model card for ren-1.0.0
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Publish the TOPv2-tuned MiniLM encoder for Ren
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initial commit
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