Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Use multiple GPUs to process queue #1816

Open
theodufort opened this issue Nov 11, 2024 · 1 comment
Open

Use multiple GPUs to process queue #1816

theodufort opened this issue Nov 11, 2024 · 1 comment

Comments

@theodufort
Copy link

I am trying to use both of my GPUs who are passed through to my docker container.

services: faster-whisper-server-cuda: image: fedirz/faster-whisper-server:latest-cuda build: dockerfile: Dockerfile.cuda context: . platforms: - linux/amd64 - linux/arm64 restart: unless-stopped ports: - 8162:8000 environment: - WHISPER__MODEL=deepdml/faster-whisper-large-v3-turbo-ct2 - WHISPER__INFERENCE_DEVICE=cuda - WHISPER__COMPUTE_TYPE=int8 - WHISPER__NUM_WORKERS=4 - WHISPER__CPU_THREADS=4 - WHISPER_DEVICE=cuda - DEFAULT_LANGUAGE=en - PRELOAD_MODELS=["deepdml/faster-whisper-large-v3-turbo-ct2"] volumes: - hugging_face_cache:/root/.cache/huggingface privileged: true deploy: resources: reservations: devices: - driver: nvidia count: all capabilities: [gpu] volumes: hugging_face_cache:
I tried everything but it won't use more than 1 GPU even if:

image

@minhthuc2502
Copy link
Collaborator

minhthuc2502 commented Nov 19, 2024

Consider adding device_index=[0,1] when set up your Dockerfile.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants