base_model: mixedbread-ai/mxbai-edge-colbert-v0-32m
license: apache-2.0
library_name: coreml
pipeline_tag: sentence-similarity
tags:
- coreml
- colbert
- multi-vector
- late-interaction
- feature-extraction
- sentence-similarity
- apple
- on-device
MXBAIEdgeColbert (Core ML)
A Core ML export of
mixedbread-ai/mxbai-edge-colbert-v0-32m
for on-device ColBERT late-interaction (multi-vector) encoding on Apple platforms.
Base model
- Base model:
mixedbread-ai/mxbai-edge-colbert-v0-32m
This repository contains only the compiled Core ML encoder (MXBAIEdgeColbert.mlmodelc).
All weights are derived from the base model above; no additional training was performed.
What was exported
The exported program wraps the base transformer plus its three ColBERT Dense
projection layers (384 → 768 → 768 → 64, no bias / no activation), producing
per-token embeddings that are L2-normalized and masked by the attention mask.
| Property | Value |
|---|---|
| Inputs | input_ids and attention_mask, int32, static shape (1, 256) |
| Output | token_embeddings (per-token, dim 64, L2-normalized, padding zeroed) |
| Compute precision | float16 |
| Minimum deployment target | iOS 18 / macOS 15 |
Tokenization and the ColBERT [Q] / [D] prefixing and skiplist masking are
performed by the host application; this model performs encoding only.
Usage
Intended for use as the encoder in an on-device ColBERT/PLAID retrieval
pipeline. Load the compiled model with Core ML, feed padded int32
input_ids / attention_mask, and read token_embeddings.
License
Released under the Apache-2.0 license, following the base model.