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fail to create a docker container #1072
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I think you need to install the nvidia-container-toolkit. That was how I got it running on my system. |
Hello, i find a problem, i use docker compose run it, use nvidia gpu version: '3.5'
services:
tabby:
restart: always
image: tabbyml/tabby
container_name: tabby
command: serve --model TabbyML/StarCoder-1B --device cuda
volumes:
- "./data:/data"
ports:
- 8080:8080
environment:
- CUDA_VISIBLE_DEVICES=0
- NVIDIA_VISIBLE_DEVICES=0
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu] sudo docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi
Mon Jan 1 14:07:33 2024
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.54.03 Driver Version: 535.54.03 CUDA Version: 12.2 |
... docker install container toolkit: i use i try use binary file running, version:https://github.com/TabbyML/tabby/releases/tag/v0.7.0
or
output
|
This sounds like you are missing the openssl libraries on your local system, it shouldn't be related to the docker error. Have you tried running it directly via docker without compose? |
We are experiencing similar issues, where we are trying to run tabby on a local server to use for multiple people, where we have a few other docker instances running (p.ex. overleaf).
But on the local server machine with the following specs, it fails silently and we can't see where it fails:
Any hints? |
Hi,could you share the log output? it'll be also helpful to provide CPU information from |
There are unfortunately no outputs from the logs - that's the major issue! It just repeats
because it is set to restart in the docker compose file. |
Hi
|
i try use
i try it, but no output anything |
@faritor Does it work if you run it on the CPU instead of the GPU? |
still so @jbigler |
Sorry for missing your response. The reason for exit immediately is that your cpu doesn't come with This is tracked in #1142 |
Describe the bug
First i install CUDA Toolkit
Then use docker order and throw a error
docker run -it --gpus all -p 8080:8080 -v $HOME/.tabby:/data tabbyml/tabby serve --model TabbyML/StarCoder-1B --device cuda
Information about your version
TabbyML/tabby latest
Information about your GPU
description: 3D controller product: GP107M [GeForce GTX 1050 Ti Mobile] [10DE:1C8C] vendor: NVIDIA Corporation [10DE] physical id: 0 bus info: pci@0000:01:00.0 version: a1 width: 64 bits clock: 33MHz capabilities: pm msi pciexpress bus_master cap_list rom configuration: driver=nvidia latency=0 resources: irq:146 memory:a3000000-a3ffffff memory:90000000-9fffffff memory:a0000000-a1ffffff ioport:4000(size=128) memory:a4000000-a407ffff *-display description: VGA compatible controller product: UHD Graphics 630 (Mobile) [8086:3E9B] vendor: Intel Corporation [8086] physical id: 2 bus info: pci@0000:00:02.0 version: 00 width: 64 bits clock: 33MHz capabilities: pciexpress msi pm vga_controller bus_master cap_list rom configuration: driver=i915 latency=0 resources: irq:137 memory:a2000000-a2ffffff memory:80000000-8fffffff ioport:5000(size=64) memory:c0000-dffff
Additional context
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