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## Add BGE-M3 (BAAI/bge-m3)

**Model**: [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3)
**Architecture**: XLM-RoBERTa (large) — 568M parameters
**Embedding dimensions**: 1024
**Max sequence length**: 8192 tokens
**Languages**: 100+

### Conversion

Converted using `optimum-cli export onnx --model BAAI/bge-m3 --task feature-extraction`.
Validated ONNX output against PyTorch: cosine similarity > 0.9999 across English,
French, and Chinese test sentences.

### Local testing

Tested with Typesense 29.0 via Docker:
- Collection creation
- Document indexing with auto-embedding
- Semantic search (English)
- Cross-lingual semantic search (French query → English results)

### Config

model_type: xlm_roberta
vocab_file_name: sentencepiece.bpe.model

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 multilingual-e5-large/model.onnx_data filter=lfs diff=lfs merge=lfs -text
+bge-m3/model.onnx_data filter=lfs diff=lfs merge=lfs -text

bge-m3/config.json

@@ -0,0 +1,4 @@
+{
+  "model_type": "xlm_roberta",
+  "vocab_file_name": "sentencepiece.bpe.model"
+}

bge-m3/model.onnx

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bge-m3/model.onnx_data

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bge-m3/sentencepiece.bpe.model

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