OpenEden Codebook Base Model
This repository stores the OpenEden 8D physiological vector to semantic codebook alignment model. It is released under AGPL-3.0 together with the OpenEden runtime.
Contents
text_encoder/: fine-tunedQwen/Qwen3-Embedding-0.6BSentenceTransformervector_projector.pt: 8D vector projector into the text embedding spacemetadata.json: training configurationevaluation.json: retrieval evaluation metricslocal-model-artifact.json: JVM runtime artifact used by the local CLILICENSE: GNU Affero General Public License v3.0
Training
- samples: 2048
- codebook nodes: 512
- base model:
Qwen/Qwen3-Embedding-0.6B - epochs: 5
- batch size: 16
- text encoder: unfrozen
Evaluation
- exactTop1: 0.12939453125
- nodeTop1: 0.509765625
- nodeTop5: 0.65478515625
The stored vector dimensions are exactly [L, P, E, S, tau, V, M, F].
Derived dissonance is not stored in this model or training data.
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from sentence_transformers import SentenceTransformer model = SentenceTransformer("0x4C57/openeden-codebook-base-model") 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]