Comments (6)
Hi, please provide repo step if possible, so that our team can help to take a look!
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- Update config to match requirements of my AWS env.
- SGs
- region
- updated
gpu_worker_g5
to includeCPU
andGPU
values.
- Deploy via Ray up
- Use Ray attach.
- Use
rayllm run --model models/continuous_batching/amazon--LightGPT.yaml
- continuous loop on deploy.
from ray-llm.
I don't believe the AMI has the drivers installed for CUDA 12. Could that be the issue?
from ray-llm.
@sihanwang41 an update on investigating this issue?
from ray-llm.
FWIW, ray-llm is not deployable in the current state on images >= 0.5.0
. This is not limited to g5.12xlarges.
from ray-llm.
+1 on this, I'm having to use 0.4.0 else DEPLOYING stuck in loop with 0.5.0 @JGSweets (thanks for your comment, got me up and running)
from ray-llm.
Related Issues (20)
- Queue-Worker System HOT 2
- Error when trying to run tensorrt model on ray HOT 1
- Podman Error on red hat 9?
- A100 not correctly detected / No available node types can fulfill resource request
- Serve a new model without restarting RayLLM HOT 1
- In the 0.5.0 release, some files appear to be missing
- Support for the Mistral based Embeddings models
- Autoscaling support in Ray-llm
- How to adjust engine kwargs from defaults values for models in `./models/`
- There should be a feature saying that all of the 3 options are wrong HOT 1
- Issue when running ray-llm with tensorrt-llm HOT 1
- RayWorkerVllm Actor Dies After ~1h: The actor is dead because all references to the actor were removed.
- `serve status` fails on the head pod after model is deployed
- Run rayllm frontend on head pod fails HOT 1
- RAY-LLM stuck at replica step HOT 1
- Error when `serve run` HOT 1
- templating serve-config and model config instead of copy and paste
- Is this project still actively being maintained? HOT 8
- Running ray-llm 0.5.0 on g4dn.12xlarge instance HOT 2
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