Instructions to use Novadata-Technologies/Reason-ModernColBERT-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Novadata-Technologies/Reason-ModernColBERT-ONNX with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Novadata-Technologies/Reason-ModernColBERT-ONNX") 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] - Notebooks
- Google Colab
- Kaggle
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library_name: colbert-onnx
tags:
- colbert
- onnx
- sentence-transformers
- feature-extraction
license: mit
---
# Reason-ModernColBERT-ONNX
ONNX export of [lightonai/Reason-ModernColBERT](https://huggingface.co/lightonai/Reason-ModernColBERT) for fast CPU inference.
## Model Details
- **Source Model**: [lightonai/Reason-ModernColBERT](https://huggingface.co/lightonai/Reason-ModernColBERT)
- **Embedding Dimension**: 128
- **Format**: ONNX (FP32)
## Files
| File | Description |
|------|-------------|
| `model.onnx` | FP32 ONNX model |
| `tokenizer.json` | Tokenizer configuration |
| `config_sentence_transformers.json` | Model configuration |
## Usage with colbert-onnx (Rust)
```rust
use colbert_onnx::Colbert;
let mut model = Colbert::from_pretrained("path/to/model")?;
let embeddings = model.encode_documents(&["Hello world"])?;
```
## Export Tool
This model was exported using [pylate-onnx-export](https://github.com/lightonai/next-plaid/tree/main/onnx/python):
```bash
pip install "pylate-onnx-export @ git+https://github.com/lightonai/next-plaid.git#subdirectory=onnx/python"
pylate-onnx-export lightonai/Reason-ModernColBERT --push-to-hub Novadata-Technologies/Reason-ModernColBERT-ONNX
```
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