Xenova/ms-marco-MiniLM-L-6-v2

Classification · served with ONNX Runtime · ↓ 683.5K downloads a month · View on Hugging Face

Versions

Smaller versions (8-bit, 4-bit) need less GPU memory and answer a little less precisely.

The same model packaged differently: a quantized version needs less GPU memory and runs on a cheaper machine.

Version	Runtime	Weights	GPU memory	Cheapest machine now
ms marco MiniLM L6 v2 (cross-encoder)cross-encoder/ms-marco-MiniLM-L6-v2	Text Embeddings Inference	50 MB	1.6 GB	$0.08/h GTX 1660 SUPER
ms marco MiniLM L4 v2 (cross-encoder)cross-encoder/ms-marco-MiniLM-L4-v2	Text Embeddings Inference	40 MB	1.5 GB	$0.08/h GTX 1660 SUPER
all MiniLM L12 v2 (sentence-transformers)sentence-transformers/all-MiniLM-L12-v2	Text Embeddings Inference	70 MB	1.6 GB	$0.08/h GTX 1660 SUPER
ms marco MiniLM L12 v2 (cross-encoder)cross-encoder/ms-marco-MiniLM-L12-v2	Text Embeddings Inference	70 MB	1.6 GB	$0.08/h GTX 1660 SUPER
ms marco MiniLM L 6 v2 (Xenova)Xenova/ms-marco-MiniLM-L-6-v2	ONNX Runtime	20 MB	1 GB	$0.08/h GTX 1660 SUPER

Deploying ONNX models from the catalog is coming soon. Today, download the files from Hugging Face and upload them in Inference.

Loading…