Export HuggingFace ColBERT models to ONNX format for Rust inference
Project description
ColBERT Export
A CLI tool to export HuggingFace ColBERT models to ONNX format for fast Rust inference.
Installation
pip install "colbert-export @ git+https://github.com/lightonai/next-plaid.git#subdirectory=onnx/python"
Usage
Export a Model
# Export a ColBERT model to ONNX format
colbert-export lightonai/GTE-ModernColBERT-v1
# Export with INT8 quantization for 2x speedup
colbert-export lightonai/GTE-ModernColBERT-v1 --quantize
# Export to a custom directory
colbert-export lightonai/GTE-ModernColBERT-v1 -o ./my-models
Quantize an Existing Model
colbert-quantize ./models/GTE-ModernColBERT-v1
Output
The tool creates a directory with the following files:
models/<model-name>/
├── model.onnx # FP32 ONNX model
├── model_int8.onnx # INT8 quantized (if --quantize)
├── tokenizer.json # Tokenizer configuration
└── config_sentence_transformers.json # Model metadata
Supported Models
lightonai/GTE-ModernColBERT-v1(128-dim, ModernBERT-based)- Any PyLate-compatible ColBERT model from HuggingFace
Python API
from colbert_export import export_model, quantize_model
# Export a model
output_dir = export_model(
model_name="lightonai/GTE-ModernColBERT-v1",
output_dir="./models",
quantize=True,
)
# Or quantize an existing model
quantize_model("./models/GTE-ModernColBERT-v1")
License
Apache-2.0
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