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all-MiniLM-L6-v2-hidden-states-exposed-v1
yaww85/all-MiniLM-L6-v2-hidden-states-exposed-v1
all-MiniLM-L6-v2-hidden-states-exposed-v1 is a feature extraction model from yaww85. Use it when you need embeddings to search or compare text. It is set up for onnxruntime. The card lists the license as apache-2.0.
A re-export of sentence-transformers/all-MiniLM-L6-v2 to ONNX format with all intermediate hidden layer outputs exposed.
Access
Public
Updated Jun 22, 2026
Repo size
90.3 MB
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0
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Repo makeup
Click a slice to open those files.
.data90.3 MB · 100%
At a glance
- Task
- Feature Extraction
- Library
- onnxruntime
- License
- apache-2.0
- Access
- Public
- Created
- Jun 22, 2026
- Updated
- Jun 22, 2026
- SHA
- ac5565ef
Base models
Model card
From the Hugging Face model README
all-MiniLM-L6-v2 — ONNX with All Hidden States
A re-export of sentence-transformers/all-MiniLM-L6-v2 to ONNX format with all intermediate hidden layer outputs exposed.
Changes from the Original
The standard HuggingFace ONNX export only includes last_hidden_state. This export sets output_hidden_states=True and wraps the model to expose all 7 hidden state layers as named outputs:
| Output | Description |
|---|---|
last_hidden_state | Final transformer layer (contextualized embeddings) |
hidden_states.0 | Input embedding layer (static, context-independent) |
hidden_states.1 — hidden_states.6 | Intermediate transformer layers |
This enables use cases that require access to both static and contextualized representations — for example, comparing layer-0 embeddings (word identity) against layer-6 embeddings (contextual meaning) for semantic analysis.
Files
| File | Description | Size |
|---|---|---|
model.onnx | ONNX model graph (opset 17) | ~57 KB |
model.onnx.data | External tensor weights | ~87 MB |
vocab.txt | WordPiece vocabulary (30,522 tokens) | ~227 KB |
Export Reproduction
This model was produced by the export script at bounded_contexts/exocortex/platform/models/minilm/export_minilm.py:
cd bounded_contexts/exocortex/platform/models/minilm
uv run python export_minilm.py
Attribution
This is a derivative of sentence-transformers/all-MiniLM-L6-v2 by Nils Reimers, licensed under Apache 2.0.
The only modification is the ONNX re-export with all hidden layer outputs enabled. No model weights were altered.
- Task
- Feature Extraction
- Library
- onnxruntime
- License
- apache-2.0
- Languages
- en
- Created
- Jun 22, 2026
- Updated
- Jun 22, 2026