BGE-M3 β€” 4-bit MLX

4-bit MLX quantization of BAAI/bge-m3, for Apple Silicon (~321 MB). Multilingual text-embedding model (1024-dim dense vectors).

Usage

pip install -U mlx-embeddings
from mlx_embeddings import load, generate

model, tokenizer = load("TyKaoz/bge-m3-4bit")
out = generate(model, tokenizer, texts=["Bonjour", "Hello", "δ½ ε₯½"])
print(out.text_embeds.shape)  # (3, 1024)
Base Tool Precision Size
BAAI/bge-m3 mlx-embeddings 4-bit Β· group 64 ~321 MB

By TyKaoz β€” privacy-first native macOS LLM chat client. Apache 2.0, inherited from the base model.

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