Comments (9)
Great thanks for looking into the AVX thing - in hindsight that was the obvious problem - I should have known π€¦
So I think the short term solution would be to build the image on the system you're targetting and the C preprocessor should pick up what instructionsets are supported. The slightly longer term solution is for me to add CI builds that build with different sets of CPU instructions and make them available as part of the release
from turbopilot.
hi @oshanz - please try changing the image uri to ghcr.io/ravenscroftj/turbopilot:latest - the path from your log above is the old build.
from turbopilot.
Hi there thanks for your ticket. Can I ask what operating system and processor architecture you are running your k8s cluster on?
from turbopilot.
Hi there thanks for your ticket. Can I ask what operating system and processor architecture you are running your k8s cluster on?
I am running Ubuntu 22.04 LTS.
Kubernetes V1.23
The CPU's support AVX (not AVX2) - some example of my node CPU's:
(48 x Intel(R) Xeon(R) CPU E5-2697 v2 @ 2.70GHz (2 Sockets), 32 x Intel(R) Xeon(R) CPU E5-2650 v2 @ 2.60GHz (2 Sockets))
- I haven't tried the container on my Ryzen system that has AVX2 support..... will try that now......
Update. No complaints on the K8 node that has (what I assume) is AVX2 support. You might want to add AVX support (plenty of powerful enough CPU's don't have AVX2 support) - gotta love bulky RAM. :D
from turbopilot.
It happened to me, too
when i run
docker run --rm -it -v /home/yang/models:/models -e MODEL="/models/codegen-2B-multi-ggml-4bit-quant.bin" -p 80:18080 ghcr.io/ravenscroftj/turbopilot/turbopilot:latest
terminal output
main: seed = 1681348410
gptj_model_load: loading model from '/models/codegen-2B-multi-ggml-4bit-quant.bin' - please wait ...
gptj_model_load: n_vocab = 51200
gptj_model_load: n_ctx = 2048
gptj_model_load: n_embd = 2560
gptj_model_load: n_head = 32
gptj_model_load: n_layer = 32
gptj_model_load: n_rot = 64
gptj_model_load: f16 = 3
Illegal instruction (core dumped)
My Operating Environment :
docker 20.10.18 Community
Ubuntu 22.04.1 LTS
Intel(R) Celeron(R) CPU J1900 @ 1.99GHz
I pulled the docker image directly
from turbopilot.
docker run --rm -it -v ./models:/models -e THREADS=6 -e MODEL="/models/codegen-6B-multi-ggml-4bit-quant.bin" -p 18080:18080 ghcr.io/ravenscroftj/turbopilot/turbopilot:latest
WARNING: The requested image's platform (linux/amd64) does not match the detected host platform (linux/arm64/v8) and no specific platform was requested
main: seed = 1681194918
gptj_model_load: loading model from '/models/codegen-6B-multi-ggml-4bit-quant.bin' - please wait ...
gptj_model_load: n_vocab = 51200
gptj_model_load: n_ctx = 2048
gptj_model_load: n_embd = 4096
gptj_model_load: n_head = 16
gptj_model_load: n_layer = 33
gptj_model_load: n_rot = 64
gptj_model_load: f16 = 2
gptj_model_load: ggml ctx size = 6325.92 MB
Illegal instruction (core dumped)
Apple M1 Pro
Mac 13.2
colima 0.5.4
from turbopilot.
@ravenscroftj same issue with above image on mac m1.
from turbopilot.
hi @4j4y - just to clarify when you say image above you are referring to ghcr.io/ravenscroftj/turbopilot:latest
(as opposed to the old image with /turbopilot/turbopilot in it)?
I don't have an apple silicon device so I'm struggling to work out what is working and what isn't. Are you running docker desktop on your m1 in order to run the image? Don't suppose you can share the output from your docker pull or docker run command (I'm after the image hash that you are using).
Finally - have you tried downloading the binary zip file from the releases page and running that? Does it give the same error?
from turbopilot.
support for older instruction sets is provided in release 0.0.5
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Related Issues (20)
- Local build failing to run (NO AVX2) HOT 3
- use WebSocket for Real-time reception
- terminated by signal SIGABRT (Abort)
- Fauxpilot client does not communicate with TurboPilot πserver
- How to use it with cuda in v0.0.5 HOT 2
- Any chance for cuda 12 support? HOT 1
- Is there any roadmap to add support for replit models? HOT 2
- Add support for StableCode
- Support Huggingface Code plugin
- "symbol not found" error in docker image running under ARM64 HOT 3
- How to build for Mac OS Apple Silicon? HOT 2
- ggml_new_tensor_impl: not enough space in the context's memory pool HOT 7
- docker turbopilot:v0.1.0-cuda12 not using gpu HOT 3
- OOM - Segmentation fault (core dumped) HOT 3
- CAN NOT RUN TURBOPILOT USING DOCKER HOT 5
- Only huggingface client works, and crashes server HOT 3
- Support for Code Llama HOT 1
- Docker Image Fail to load model
- Failed to load model wizardcoder (Illegal Instruction)
- [Feature request] Add refact model
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