metadata
license: apache-2.0
tags:
- coreml
- sentence-transformers
- embedding
- code
- bert
base_model: bigcode/starencoder
library_name: coremltools
pipeline_tag: feature-extraction
starencoder — CoreML (.mlpackage)
CoreML conversion of bigcode/starencoder for native Apple Neural Engine / GPU inference on macOS and iOS.
Files
| File | Description |
|---|---|
model.mlpackage/ |
CoreML model (FP16, flexible shapes) |
tokenizer.json |
HF fast tokenizer |
Details
- Architecture: BERT (encoder-only, trained on The Stack code dataset)
- Precision: FP16 (native ANE precision)
- Compute units:
.all— CoreML schedules across ANE, GPU, and CPU - Input shapes: batch=1..512, seq_len=1..1024 (flexible range)
- Embedding dimension: 768
Usage with cai
cai index --embed-backend swift --embed-model "rsvalerio/starencoder-coreml"
The Swift backend downloads the .mlpackage from this repo, compiles it to .mlmodelc on first run (~30-60s), and caches the compiled model for subsequent runs.
Conversion
Converted using rsvalerio/models CI pipeline with coremltools.
pip install coremltools transformers torch
python convert.py