How much GPU memory does static-retrieval-mrl-en-v1 need?

About 1.2 GB: 0.13 GB of weights and the runtime's own memory.

What is the cheapest GPU to run static-retrieval-mrl-en-v1?

Right now one GTX 1070 at $0.06 an hour; RTX 5090 at $0.71 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.

Can static-retrieval-mrl-en-v1 run on an RTX 4090?

Yes: it needs about 1.2 GB and an RTX 4090 has 24 GB.

Models / static-retrieval-mrl-en

sentence-transformers/static-retrieval-mrl-en-v1

Embeddings · served with ONNX Runtime · ↓ 0 downloads a month · View on Hugging Face

sentence-transformers/static-retrieval-mrl-en-v1 needs about 1.2 GB of GPU memory. It runs on one GTX 1070 from $0.06/h right now; best value: RTX 5090 at $0.71/h.

Weights: 130 MB
GPU memory needed: about 1.2 GB
Memory · disk: 8 GB · 30 GB
Licence: apache-2.0

Versions

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

full precisiononnx/model.onnx130 MB · 1.2 GB GPU 4-bit (bnb)onnx/model_bnb4.onnx130 MB · 1.2 GB GPU float16onnx/model_fp16.onnx60 MB · 1.1 GB GPU 8-bitonnx/model_int8.onnx30 MB · 1 GB GPU 4-bitonnx/model_q4.onnx130 MB · 1.2 GB GPU 4-bit, float16onnx/model_q4f16.onnx60 MB · 1.1 GB GPU 8-bitonnx/model_quantized.onnx30 MB · 1 GB GPU 8-bitonnx/model_uint8.onnx30 MB · 1 GB GPU

Hardware and deploy

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

Questions

How much GPU memory does static-retrieval-mrl-en-v1 need?: About 1.2 GB: 0.13 GB of weights and the runtime's own memory.
What is the cheapest GPU to run static-retrieval-mrl-en-v1?: Right now one GTX 1070 at $0.06 an hour; RTX 5090 at $0.71 an hour is the best value for its speed. Prices are live offers from GPU clouds, checked every 15 minutes.
Can static-retrieval-mrl-en-v1 run on an RTX 4090?: Yes: it needs about 1.2 GB and an RTX 4090 has 24 GB.

Loading…