Trying to use this with local llms but there is no easy way to figure it out. #1295

dreemur99 · 2023-09-29T16:01:50Z

The option for setting up your own model is there but you cant point it to an actually directory or llm file directly? Why not?

cognitivebot · 2023-10-03T05:56:24Z

Hey @dreemur99, you can select the exisitng models in the drop down, additionally you can also add models hosted on huggingface & replicate. We're working to add custom local llm support in the upcoming v0.0.14 release

mohcineelharras · 2023-11-04T21:05:45Z

It's out guys, you can go and try it out !
I made some changes to the docker file and docker compose files, this way I can run it with gpu acceleration
It's working perfectly well

docker-compose.yaml

version: '3.8'
services:
backend:
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids: ['0']
capabilities: [gpu]
volumes:
- "./:/app"
- "/home/mohcine/work/cloned/textgen/models/dolphin-2.2.1-mistral-7b.Q5_K_M.gguf:/app/local_model_path"
build: .
depends_on:
- super__redis
- super__postgres
networks:
- super_network
command: ["/app/wait-for-it.sh", "super__postgres:5432","-t","60","--","/app/entrypoint.sh"]
celery:
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids: ['0']
capabilities: [gpu]
volumes:
- "./:/app"
- "${EXTERNAL_RESOURCE_DIR:-./workspace}:/app/ext"
- "/home/mohcine/work/cloned/textgen/models/dolphin-2.2.1-mistral-7b.Q5_K_M.gguf:/app/local_model_path"
build: .
depends_on:
- super__redis
- super__postgres
networks:
- super_network
command: ["/app/entrypoint_celery.sh"]
gui:
build:
context: ./gui
args:
NEXT_PUBLIC_API_BASE_URL: "/api"
networks:
- super_network
super__redis:
image: "redis/redis-stack-server:latest"
networks:
- super_network
volumes:
- redis_data:/data

super__postgres:
image: "docker.io/library/postgres:16"
environment:
- POSTGRES_USER=superagi
- POSTGRES_PASSWORD=password
- POSTGRES_DB=super_agi_main
volumes:
- superagi_postgres_data:/var/lib/postgresql/data/
networks:
- super_network

proxy:
image: nginx:stable-alpine
ports:
- "3000:80"
networks:
- super_network
depends_on:
- backend
- gui
volumes:
- ./nginx/default.conf:/etc/nginx/conf.d/default.conf

networks:
super_network:
driver: bridge
volumes:
superagi_postgres_data:
redis_data:

Dockerfile :

FROM nvidia/cuda:12.1.0-devel-ubuntu22.04 AS compile-image
WORKDIR /app

RUN apt-get update && apt-get install --no-install-recommends -y
git vim build-essential python3-dev python3-venv python3-pip

RUN apt-get update &&
apt-get install --no-install-recommends -y wget libpq-dev gcc g++ &&
apt-get clean &&
rm -rf /var/lib/apt/lists/*

RUN python3 -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"

COPY requirements.txt .
RUN pip3 install --upgrade pip &&
pip3 install --upgrade pip setuptools wheel ninja
RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
RUN CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip install llama-cpp-python --force-reinstall --upgrade --no-cache-dir --verbose

RUN pip3 install -r requirements.txt
#pip3 install --no-cache-dir -r requirements.txt
RUN python3 -m nltk.downloader averaged_perceptron_tagger punkt

COPY . .

RUN chmod +x ./entrypoint.sh ./wait-for-it.sh ./install_tool_dependencies.sh ./entrypoint_celery.sh

FROM nvidia/cuda:12.1.0-devel-ubuntu22.04 AS build-image
WORKDIR /app

RUN apt-get update && apt-get install --no-install-recommends -y
git vim build-essential python3-dev python3-venv python3-pip

ENV LLAMA_CUBLAS=1

RUN apt-get update &&
apt-get install --no-install-recommends -y libpq-dev &&
apt-get clean &&
rm -rf /var/lib/apt/lists/*

COPY --from=compile-image /opt/venv /opt/venv
COPY --from=compile-image /app /app
COPY --from=compile-image /root/nltk_data /root/nltk_data

ENV PATH="/opt/venv/bin:$PATH"

EXPOSE 8001

yf007 · 2023-12-24T15:19:39Z

I'm trying to figure out how to run it on Windows 11.
I can't get the full address into my C drive.
"C:\1\dolphin-2.5-mixtral-8x7b.Q5_K_M.gguf"

chatgpt Told me to try this:

volumes:
  - "./:/app"
  - "C:/1/dolphin-2.5-mixtral-8x7b.Q5_K_M.gguf:/app/local_model_path/dolphin-2.5-mixtral-8x7b.Q5_K_M.gguf"
build: .
depends_on:
  - super__redis
  - super__postgres
networks:
  - super_network
command: ["/app/wait-for-it.sh", "super__postgres:5432", "-t", "60", "--", "/app/entrypoint.sh"]

celery:
volumes:
- "./:/app"
- "${EXTERNAL_RESOURCE_DIR:-./workspace}:/app/ext"
- "C:/1/dolphin-2.5-mixtral-8x7b.Q5_K_M.gguf:/app/local_model_path/dolphin-2.5-mixtral-8x7b.Q5_K_M.gguf"
build: .
"

etc.

but I get a 404 error"

backend-1 | INFO: 172.27.0.7:45762 - "GET /models_controller/test_local_llm HTTP/1.0" 404 Not Found
proxy-1 | 172.27.0.1 - - [24/Dec/2023:15:11:43 +0000] "GET /api/models_controller/test_local_llm HTTP/1.1" 404 87 "http://127.0.0.1:3000/" "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" "-"

What am I missing here?
I'm sorry, but I don't understand paths except for Windows...

alfi4000 · 2023-12-26T08:40:00Z

I have same issue at linux with the exact same model!

alfi4000 · 2023-12-26T08:40:17Z

I think the llm isn't compatible!

alfi4000 · 2023-12-26T09:20:31Z

at my end at the backend I just saw the errorr but Idk how to solve it: superagi-backend-1 | gguf_init_from_file: invalid magic number 00000000
superagi-backend-1 | error loading model: llama_model_loader: failed to load model from /app/local_model_path
superagi-backend-1 |
superagi-backend-1 | llama_load_model_from_file: failed to load model
superagi-backend-1 | 2023-12-26 09:19:35 UTC - Super AGI - ERROR - [/app/superagi/helper/llm_loader.py:27] -
superagi-backend-1 | 2023-12-26 09:19:35 UTC - Super AGI - ERROR - [/app/superagi/controllers/models_controller.py:185] - Model not found.
superagi-backend-1 | 2023-12-26 09:19:35 UTC - Super AGI - INFO - [/app/superagi/controllers/models_controller.py:203] - Error:
superagi-backend-1 | 2023-12-26 09:19:35 UTC - Super AGI - INFO - [/app/superagi/controllers/models_controller.py:203] -
superagi-backend-1 | INFO: 172.19.0.7:43076 - "GET /models_controller/test_local_llm HTTP/1.0" 404 Not Found

StylizeR · 2024-01-03T00:57:03Z

I do not see a dropdown to select a local LLM.
Also getting: gguf_init_from_file: invalid magic number 00000000

I guess it's because no model is selected?

Any idea how to get it working? I tried to add multiple gguf in the folder and adding it to the volumes.

StylizeR · 2024-01-03T01:11:19Z

I do not see a dropdown to select a local LLM. Also getting: gguf_init_from_file: invalid magic number 00000000

I guess it's because no model is selected?

Any idea how to get it working? I tried to add multiple gguf in the folder and adding it to the volumes.

Ok, I see what I did wrong.

You have to mount the gguf to the file local_model_path, not mount the directory to local_model_path.

volumes: - ./local_model_path/your-model.gguf:/app/local_model_path

alfi4000 · 2024-01-08T06:43:01Z

dude i am a bit confused can you help me out with this maybe would be great since in no forum I got an answer or any help! so the thing is the my llm is in the path home/cronos/llms

this is the docker-compose.yaml:

version: '3.8'
services:
backend:
volumes:
- "./:/app"
- "./local_model_path/dolphin-2-5-mixtral-8x7b-Q2_K.gguf:/app/local_model_path"
build: .
depends_on:
- super__redis
- super__postgres
networks:
- super_network
command: ["/app/wait-for-it.sh", "super__postgres:5432","-t","60","--","/app/entrypoint.sh"]
celery:
volumes:
- "./:/app"
- "${EXTERNAL_RESOURCE_DIR:-./workspace}:/app/ext"
- "./home/cronos/llms/dolphin-2-5-mixtral-8x7b-Q2_K.gguf:/app/local_model_path"

alfi4000 · 2024-01-08T06:46:42Z

i don't get what I am doing wrong I just first did the exact thing like in the video but that wasn't working for me so I researched but wasn't finding any answer anywhere and comment some issues because some had a close same error to me so though they can help me but no answer! huh I just cant anymore I spent like 30hours to get it work!

yf007 · 2024-01-08T08:35:04Z

Look at the comments on the YouTube video and it turns out that no one there was able to get it to work. I think that if they manage to make it work locally, even at the level of selecting a file from the computer, this is what will make the big leap in the field! I hope someone is working on it these days בתאריך יום ב׳, 8 בינו׳ 2024, 08:46, מאת alfi4000 ***@***.***

…

: i don't get what I am doing wrong I just first did the exact thing like in the video but that wasn't working for me so I researched but wasn't finding any answer anywhere and comment some issues because some had a close same error to me so though they can help me but no answer! huh I just cant anymore I spent like 30hours to get it work! — Reply to this email directly, view it on GitHub <#1295 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AELRYWIF4RGXDMLM75XCPFDYNOI5ZAVCNFSM6AAAAAA5MVUC5OVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTQOBQGQ2TSOJWG4> . You are receiving this because you commented.Message ID: ***@***.***>

yf007 · 2024-01-08T08:37:24Z

I mean that a simple user without technological knowledge can choose A file that contains a model that he will select from the computer and will work on all types of platforms, Windows/Linux/Mac, etc., etc. בתאריך יום ב׳, 8 בינו׳ 2024, 10:34, מאת ***@***.***>:

…

Look at the comments on the YouTube video and it turns out that no one there was able to get it to work. I think that if they manage to make it work locally, even at the level of selecting a file from the computer, this is what will make the big leap in the field! I hope someone is working on it these days בתאריך יום ב׳, 8 בינו׳ 2024, 08:46, מאת alfi4000 ‏< ***@***.***>: > i don't get what I am doing wrong I just first did the exact thing like > in the video but that wasn't working for me so I researched but wasn't > finding any answer anywhere and comment some issues because some had a > close same error to me so though they can help me but no answer! huh I just > cant anymore I spent like 30hours to get it work! > > — > Reply to this email directly, view it on GitHub > <#1295 (comment)>, > or unsubscribe > <https://github.com/notifications/unsubscribe-auth/AELRYWIF4RGXDMLM75XCPFDYNOI5ZAVCNFSM6AAAAAA5MVUC5OVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTQOBQGQ2TSOJWG4> > . > You are receiving this because you commented.Message ID: > ***@***.***> >

dreemur99 · 2024-01-10T03:13:56Z

I don't get it. You can pick localllm in new model but you still can't point a path the local model you have? What's changed? Am I missing something bc I dont see any info on the main page.

rounak610 · 2024-01-13T06:28:18Z

@yf007
add your model path in this format: "C:/1/dolphin-2.5-mixtral-8x7b.Q5_K_M.gguf:/app/local_model_path"
add your model path in both celery and backend volumes as shown in the video
We have added multi-gpu support with this pr #1391
you need to run this command to run local llms: docker compose -f docker-compose-gpu.yml up --build

alfi4000 · 2024-01-17T07:15:49Z

lol at my end this file with gpu at the end doesn't exists let me check if there is an update available I could swear I am up to date!

alfi4000 · 2024-01-17T07:16:57Z

Look at the comments on the YouTube video and it turns out that no one there was able to get it to work. I think that if they manage to make it work locally, even at the level of selecting a file from the computer, this is what will make the big leap in the field! I hope someone is working on it these days בתאריך יום ב׳, 8 בינו׳ 2024, 08:46, מאת alfi4000 @.***
…
: i don't get what I am doing wrong I just first did the exact thing like in the video but that wasn't working for me so I researched but wasn't finding any answer anywhere and comment some issues because some had a close same error to me so though they can help me but no answer! huh I just cant anymore I spent like 30hours to get it work! — Reply to this email directly, view it on GitHub <#1295 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/AELRYWIF4RGXDMLM75XCPFDYNOI5ZAVCNFSM6AAAAAA5MVUC5OVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTQOBQGQ2TSOJWG4 . You are receiving this because you commented.Message ID: @.***>

yeah I already have seen that and was wondering because some many people were exiting about it! but also no video only from SuperAGI how to get it to work locally!

alfi4000 · 2024-01-17T07:26:36Z

hehe lol now I was trying to get SuperAGI up to date and saw there isn't any button to update or command, now just replaced all files with the actual ones in the repository! Huh

alfi4000 · 2024-01-17T07:28:10Z

I now hope that it works!

alfi4000 · 2024-01-17T07:37:10Z

Lol now I got this error: Error response from daemon: could not select device driver "nvidia" with capabilities: [[gpu]]
That came when I executed: sudo docker compose -f docker-compose-gpu.yml up --build
I used a Nvidia Tesla p40 24gb vram!

What is that I dont get this why this happened!?

alfi4000 · 2024-01-17T07:38:25Z

version: '3.8'
services:
backend:
volumes:
- "./:/app"
- "/home/kali/llms/dolphin-2-5-mixtral-8x7b-Q2_K.gguf:/app/local_model_path"
build:
context: .
dockerfile: Dockerfile-gpu
depends_on:
- super__redis
- super__postgres
networks:
- super_network
command: ["/app/wait-for-it.sh", "super__postgres:5432","-t","60","--","/app/entrypoint.sh"]
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]

celery:
volumes:
- "./:/app"
- "${EXTERNAL_RESOURCE_DIR:-./workspace}:/app/ext"
- "/home/kali/llms/dolphin-2-5-mixtral-8x7b-Q2_K.gguf:/app/local_model_path"
build:
context: .
dockerfile: Dockerfile-gpu
depends_on:
- super__redis
- super__postgres
networks:
- super_network
command: ["/app/entrypoint_celery.sh"]
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
gui:
build:
context: ./gui
args:
NEXT_PUBLIC_API_BASE_URL: "/api"
networks:
- super_network

volumes:

- ./gui:/app

- /app/node_modules/

- /app/.next/

super__redis:
image: "redis/redis-stack-server:latest"
networks:
- super_network

uncomment to expose redis port to host

ports:

- "6379:6379"

volumes:
  - redis_data:/data

super__postgres:
image: "docker.io/library/postgres:15"
environment:
- POSTGRES_USER=superagi
- POSTGRES_PASSWORD=password
- POSTGRES_DB=super_agi_main
volumes:
- superagi_postgres_data:/var/lib/postgresql/data/
networks:
- super_network

uncomment to expose postgres port to host

ports:

- "5432:5432"

proxy:
image: nginx:stable-alpine
ports:
- "3000:80"
networks:
- super_network
depends_on:
- backend
- gui
volumes:
- ./nginx/default.conf:/etc/nginx/conf.d/default.conf

networks:
super_network:
driver: bridge
volumes:
superagi_postgres_data:
redis_data:

that's the docker-compose-gpu.yml

alfi4000 · 2024-01-17T07:40:09Z

the llm ist stored in /home/kali/llms/
model: dolphin-2-5-mixtral-8x7b-Q2_K.gguf

alfi4000 · 2024-01-17T08:02:46Z

So now finally an error the model is in the directory: /home/kali/llms
- "/home/kali/llms/dolphin-2-5-mixtral-8x7b-Q2_K.gguf/:/app/local_model_path"
that I pasted in the gpu file but I got this error:

Error response from daemon: failed to create task for container: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error mounting "/home/kali/llms/dolphin-2-5-mixtral-8x7b-Q2_K.gguf" to rootfs at "/app/local_model_path": mount /home/kali/llms/dolphin-2-5-mixtral-8x7b-Q2_K.gguf:/app/local_model_path (via /proc/self/fd/6), flags: 0x5000: not a directory: unknown: Are you trying to mount a directory onto a file (or vice-versa)? Check if the specified host path exists and is the expected type

Someone of the support might be feel free to help me I am using ubuntu server 22.04.3!
i am unsure what I am doing wrong!

alfi4000 · 2024-01-17T08:05:10Z

a easier way for end users would might be for local llms like Autogenstudio just a thought!

I love Autogenstudio but not like SuperAGI nice tools just basic stuff is still available why that I would prefer on SuperAGI!

rounak610 · 2024-01-17T18:11:22Z

@alfi4000 hey are you sure that this path exists: "/home/kali/llms/dolphin-2-5-mixtral-8x7b-Q2_K.gguf" ?
while testing I was using "/home/ubuntu/models/vicuna-7B-v1.5-GGUF/vicuna-7b-v1.5.Q5_K_M.gguf:/app/local_model_path"
and it was working fine for me, I also checked your docker-compose-gpu.yml file it looks fine

alfi4000 · 2024-01-17T20:53:44Z

have you the model inside of the SuperAGI folder? I have it outside of the SuperAGI folder!
that would be my question do the model needs to be inside of a folder in the SuperAGI folder where the docker compose file is or can it be outside because I have it outside!

that's might be the thing I am doing wrong!

alfi4000 · 2024-01-17T20:58:47Z

here check the screenshot that is what I did!

alfi4000 · 2024-01-18T03:03:01Z

I hope I am not too much confusing!

alfi4000 · 2024-01-18T03:38:35Z

I just saw that it has in the SuperAGI folder has it created that path just without the model exactly the path I wrote in the docker compose file I told to my self whate f*** is here going on!

alfi4000 · 2024-01-18T03:55:16Z

I am finally done with it I wasted now 1hour to try a few things but no solution so maybe someone here answers or I will check in a few months the repo if there is an update that there is an easter way to do that, I will check the next few days for answers then I am done with it if no ones say something !

rounak610 · 2024-01-18T06:14:19Z

no your model doesnt need to be in the superagi folder, it can be anywhere.
are you sure that your model path is correct? bcz when I was using vicuna 7B gguf model, it had a folder and then inside that folder there were multiple gguf files and I tried with q5_k_m
in your case I can see that the gguf file is in "llms" folder have you deleted the other files?
could you attach a screenshot of the contents of the llms folder, also run "pwd" command inside the llms folder so that you can get the correct path

alfi4000 · 2024-01-18T07:41:38Z

no I had not deleted the other folders inside but I created in that folder today another one where I putted the model in but it wasn't working i'll show you some screenshots!
Let me know if I should try the model you used if possible give me the link to yours so that I download the right one! :)

alfi4000 · 2024-01-18T07:42:27Z

I think the vicuna model is might be the only one yet supported or I did something wrong what I don't know!

rounak610 · 2024-01-18T09:45:35Z

@alfi4000
from the screenshots i can see that the correct path for the model should be: /home/kali/llms/dolphin-2-5-mixtral-8x7b-GGUF/dolphin-2-5-mixtral-8x7b-Q2_K.gguf
but you were using: /home/kali/llms/dolphin-2-5-mixtral-8x7b-Q2_K.gguf
I have also tested it with other gguf models and it was working fine
after correcting the model path run this command again: docker compose -f docker-compose-gpu.yml up --build

alfi4000 · 2024-01-18T16:56:25Z

Look at the second screenshot I had changed the path to the correct one!
The problem is might that I choosed one of the last options they need like I think it was close to 100gb ram I have 256gb ram I don't get it!

alfi4000 · 2024-01-18T16:57:12Z

I will try 2 different versions of that model and reach you back just to make sure that the model isn't the problem!

alfi4000 · 2024-01-18T17:49:13Z

Hmm i tried 2 not so heavy versions of it but I get every time the same error: Error response from daemon: failed to create task for container: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error mounting "/home/kali/llms/llms-test/mixtral-8x7b-v0.1.Q3_K_M.gguf" to rootfs at "/app/local_model_path": mount /home/kali/llms/llms-test/mixtral-8x7b-v0.1.Q3_K_M.gguf:/app/local_model_path (via /proc/self/fd/6), flags: 0x5000: not a directory: unknown: Are you trying to mount a directory onto a file (or vice-versa)? Check if the specified host path exists and is the expected type

alfi4000 · 2024-01-18T19:00:53Z

Here is a screen video recording that might help you : https://youtu.be/_u-8bwoKHQc

rounak610 · 2024-01-19T18:26:59Z

in the video i saw that you were getting error: str can't be interpreted as integer
this issue has been resolved in #1393
could you please take the latest pull of "main" branch and try again

alfi4000 · 2024-01-20T04:42:00Z

i have done it I replaced the hole superego folder with every file in it with the latest repo files but look by your self the log!:

superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 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superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 superagi-backend-1 | llama_model_loader: loaded meta data with 25 key-value pairs and 995 tensors from /app/local_model_path (version unknown)
| llama_model_loader: - tensor 0: token_embd.weight q3_K [ 4096, 32000, 1, 1 ]
| llama_model_loader: - tensor 1: blk.0.ffn_gate.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 2: blk.0.ffn_down.0.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 3: blk.0.ffn_up.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 4: blk.0.ffn_gate.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 5: blk.0.ffn_down.1.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 6: blk.0.ffn_up.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 7: blk.0.ffn_gate.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 8: blk.0.ffn_down.2.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 9: blk.0.ffn_up.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 10: blk.0.ffn_gate.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 11: blk.0.ffn_down.3.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 12: blk.0.ffn_up.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 13: blk.0.ffn_gate.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 14: blk.0.ffn_down.4.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 15: blk.0.ffn_up.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 16: blk.0.ffn_gate.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 17: blk.0.ffn_down.5.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 18: blk.0.ffn_up.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 19: blk.0.ffn_gate.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 20: blk.0.ffn_down.6.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 21: blk.0.ffn_up.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 22: blk.0.ffn_gate.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 23: blk.0.ffn_down.7.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 24: blk.0.ffn_up.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 25: blk.0.ffn_gate_inp.weight f16 [ 4096, 8, 1, 1 ]
| llama_model_loader: - tensor 26: blk.0.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 27: blk.0.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 28: blk.0.attn_k.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 29: blk.0.attn_output.weight q4_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 30: blk.0.attn_q.weight q3_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 31: blk.0.attn_v.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 32: blk.1.ffn_gate.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 33: blk.1.ffn_down.0.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 34: blk.1.ffn_up.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 35: blk.1.ffn_gate.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 36: blk.1.ffn_down.1.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 37: blk.1.ffn_up.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 38: blk.1.ffn_gate.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 39: blk.1.ffn_down.2.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 40: blk.1.ffn_up.2.weight q3_K [ 4096, 14336, 1, 1 ]
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| llama_model_loader: - tensor 810: blk.26.ffn_gate.1.weight q3_K [ 4096, 14336, 1, 1 ]
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| llama_model_loader: - tensor 813: blk.26.ffn_gate.2.weight q3_K [ 4096, 14336, 1, 1 ]
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| llama_model_loader: - tensor 818: blk.26.ffn_up.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 819: blk.26.ffn_gate.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 820: blk.26.ffn_down.4.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 821: blk.26.ffn_up.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 822: blk.26.ffn_gate.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 823: blk.26.ffn_down.5.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 824: blk.26.ffn_up.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 825: blk.26.ffn_gate.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 826: blk.26.ffn_down.6.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 827: blk.26.ffn_up.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 828: blk.26.ffn_gate.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 829: blk.26.ffn_down.7.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 830: blk.26.ffn_up.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 831: blk.26.ffn_gate_inp.weight f16 [ 4096, 8, 1, 1 ]
| llama_model_loader: - tensor 832: blk.26.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 833: blk.26.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 834: blk.26.attn_k.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 835: blk.26.attn_output.weight q4_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 836: blk.26.attn_q.weight q3_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 837: blk.26.attn_v.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 838: blk.27.ffn_gate.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 839: blk.27.ffn_down.0.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 840: blk.27.ffn_up.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 841: blk.27.ffn_gate.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 842: blk.27.ffn_down.1.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 843: blk.27.ffn_gate_inp.weight f16 [ 4096, 8, 1, 1 ]
| llama_model_loader: - tensor 844: blk.27.attn_k.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 845: blk.27.attn_output.weight q4_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 846: blk.27.attn_q.weight q3_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 847: blk.27.attn_v.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 848: blk.27.ffn_up.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 849: blk.27.ffn_gate.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 850: blk.27.ffn_down.2.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 851: blk.27.ffn_up.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 852: blk.27.ffn_gate.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 853: blk.27.ffn_down.3.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 854: blk.27.ffn_up.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 855: blk.27.ffn_gate.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 856: blk.27.ffn_down.4.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 857: blk.27.ffn_up.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 858: blk.27.ffn_gate.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 859: blk.27.ffn_down.5.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 860: blk.27.ffn_up.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 861: blk.27.ffn_gate.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 862: blk.27.ffn_down.6.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 863: blk.27.ffn_up.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 864: blk.27.ffn_gate.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 865: blk.27.ffn_down.7.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 866: blk.27.ffn_up.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 867: blk.27.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 868: blk.27.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 869: blk.28.ffn_gate.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 870: blk.28.ffn_down.0.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 871: blk.28.ffn_up.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 872: blk.28.ffn_gate.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 873: blk.28.ffn_down.1.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 874: blk.28.ffn_up.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 875: blk.28.ffn_gate.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 876: blk.28.ffn_down.2.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 877: blk.28.ffn_up.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 878: blk.28.ffn_gate.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 879: blk.28.ffn_down.3.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 880: blk.28.ffn_up.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 881: blk.28.ffn_gate.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 882: blk.28.ffn_down.4.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 883: blk.28.ffn_up.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 884: blk.28.ffn_gate.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 885: blk.28.ffn_down.5.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 886: blk.28.ffn_up.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 887: blk.28.ffn_gate.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 888: blk.28.ffn_down.6.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 889: blk.28.ffn_up.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 890: blk.28.ffn_gate.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 891: blk.28.ffn_gate_inp.weight f16 [ 4096, 8, 1, 1 ]
| llama_model_loader: - tensor 892: blk.28.attn_k.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 893: blk.28.attn_output.weight q4_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 894: blk.28.attn_q.weight q3_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 895: blk.28.attn_v.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 896: blk.28.ffn_down.7.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 897: blk.28.ffn_up.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 898: blk.28.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 899: blk.28.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 900: blk.29.ffn_gate.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 901: blk.29.ffn_down.0.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 902: blk.29.ffn_up.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 903: blk.29.ffn_gate.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 904: blk.29.ffn_down.1.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 905: blk.29.ffn_up.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 906: blk.29.ffn_gate.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 907: blk.29.ffn_down.2.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 908: blk.29.ffn_up.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 909: blk.29.ffn_gate.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 910: blk.29.ffn_down.3.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 911: blk.29.ffn_up.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 912: blk.29.ffn_gate.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 913: blk.29.ffn_down.4.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 914: blk.29.ffn_up.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 915: blk.29.ffn_gate.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 916: blk.29.ffn_down.5.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 917: blk.29.ffn_up.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 918: blk.29.ffn_gate.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 919: blk.29.ffn_down.6.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 920: blk.29.ffn_up.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 921: blk.29.ffn_gate.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 922: blk.29.ffn_down.7.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 923: blk.29.ffn_up.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 924: blk.29.ffn_gate_inp.weight f16 [ 4096, 8, 1, 1 ]
| llama_model_loader: - tensor 925: blk.29.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 926: blk.29.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 927: blk.29.attn_k.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 928: blk.29.attn_output.weight q4_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 929: blk.29.attn_q.weight q3_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 930: blk.29.attn_v.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 931: blk.30.ffn_gate.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 932: blk.30.ffn_down.0.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 933: blk.30.ffn_up.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 934: blk.30.ffn_gate.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 935: blk.30.ffn_down.1.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 936: blk.30.ffn_up.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 937: blk.30.ffn_gate.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 938: blk.30.ffn_down.2.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 939: blk.30.ffn_up.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 940: blk.30.ffn_gate.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 941: blk.30.ffn_down.3.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 942: blk.30.ffn_up.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 943: blk.30.ffn_gate.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 944: blk.30.ffn_down.4.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 945: blk.30.ffn_up.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 946: blk.30.ffn_gate_inp.weight f16 [ 4096, 8, 1, 1 ]
| llama_model_loader: - tensor 947: blk.30.attn_k.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 948: blk.30.attn_output.weight q4_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 949: blk.30.attn_q.weight q3_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 950: blk.30.attn_v.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 951: output.weight q6_K [ 4096, 32000, 1, 1 ]
| llama_model_loader: - tensor 952: blk.30.ffn_gate.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 953: blk.30.ffn_down.5.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 954: blk.30.ffn_up.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 955: blk.30.ffn_gate.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 956: blk.30.ffn_down.6.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 957: blk.30.ffn_up.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 958: blk.30.ffn_gate.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 959: blk.30.ffn_down.7.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 960: blk.30.ffn_up.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 961: blk.30.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 962: blk.30.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 963: blk.31.ffn_gate.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 964: blk.31.ffn_down.0.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 965: blk.31.ffn_up.0.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 966: blk.31.ffn_gate.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 967: blk.31.ffn_down.1.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 968: blk.31.ffn_up.1.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 969: blk.31.ffn_gate.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 970: blk.31.ffn_down.2.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 971: blk.31.ffn_up.2.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 972: blk.31.ffn_gate.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 973: blk.31.ffn_down.3.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 974: blk.31.ffn_up.3.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 975: blk.31.ffn_gate.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 976: blk.31.ffn_down.4.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 977: blk.31.ffn_up.4.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 978: blk.31.ffn_gate.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 979: blk.31.ffn_down.5.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 980: blk.31.ffn_up.5.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 981: blk.31.ffn_gate.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 982: blk.31.ffn_down.6.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 983: blk.31.ffn_up.6.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 984: blk.31.ffn_gate.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 985: blk.31.ffn_down.7.weight q3_K [ 14336, 4096, 1, 1 ]
| llama_model_loader: - tensor 986: blk.31.ffn_up.7.weight q3_K [ 4096, 14336, 1, 1 ]
| llama_model_loader: - tensor 987: blk.31.ffn_gate_inp.weight f16 [ 4096, 8, 1, 1 ]
| llama_model_loader: - tensor 988: blk.31.attn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 989: blk.31.ffn_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - tensor 990: blk.31.attn_k.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 991: blk.31.attn_output.weight q4_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 992: blk.31.attn_q.weight q3_K [ 4096, 4096, 1, 1 ]
| llama_model_loader: - tensor 993: blk.31.attn_v.weight q8_0 [ 4096, 1024, 1, 1 ]
| llama_model_loader: - tensor 994: output_norm.weight f32 [ 4096, 1, 1, 1 ]
| llama_model_loader: - kv 0: general.architecture str
| llama_model_loader: - kv 1: general.name str
| llama_model_loader: - kv 2: llama.context_length u32
| llama_model_loader: - kv 3: llama.embedding_length u32
| llama_model_loader: - kv 4: llama.block_count u32
| llama_model_loader: - kv 5: llama.feed_forward_length u32
| llama_model_loader: - kv 6: llama.rope.dimension_count u32
| llama_model_loader: - kv 7: llama.attention.head_count u32
| llama_model_loader: - kv 8: llama.attention.head_count_kv u32
| llama_model_loader: - kv 9: llama.expert_count u32
| llama_model_loader: - kv 10: llama.expert_used_count u32
| llama_model_loader: - kv 11: llama.attention.layer_norm_rms_epsilon f32
| llama_model_loader: - kv 12: llama.rope.freq_base f32
| llama_model_loader: - kv 13: general.file_type u32
| llama_model_loader: - kv 14: tokenizer.ggml.model str
| llama_model_loader: - kv 15: tokenizer.ggml.tokens arr
| llama_model_loader: - kv 16: tokenizer.ggml.scores arr
| llama_model_loader: - kv 17: tokenizer.ggml.token_type arr
| llama_model_loader: - kv 18: tokenizer.ggml.bos_token_id u32
| llama_model_loader: - kv 19: tokenizer.ggml.eos_token_id u32
| llama_model_loader: - kv 20: tokenizer.ggml.unknown_token_id u32
| llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32
| llama_model_loader: - kv 22: tokenizer.ggml.add_bos_token bool
| llama_model_loader: - kv 23: tokenizer.ggml.add_eos_token bool
| llama_model_loader: - kv 24: general.quantization_version u32
| llama_model_loader: - type f32: 65 tensors
| llama_model_loader: - type f16: 32 tensors
| llama_model_loader: - type q8_0: 64 tensors
| llama_model_loader: - type q3_K: 801 tensors
| llama_model_loader: - type q4_K: 32 tensors
| llama_model_loader: - type q6_K: 1 tensors
| llm_load_print_meta: format = unknown
| llm_load_print_meta: arch = llama
| llm_load_print_meta: vocab type = SPM
| llm_load_print_meta: n_vocab = 32000
| llm_load_print_meta: n_merges = 0
| llm_load_print_meta: n_ctx_train = 32768
| llm_load_print_meta: n_ctx = 4096
| llm_load_print_meta: n_embd = 4096
| llm_load_print_meta: n_head = 32
| llm_load_print_meta: n_head_kv = 8
| llm_load_print_meta: n_layer = 32
| llm_load_print_meta: n_rot = 128
| llm_load_print_meta: n_gqa = 4
| llm_load_print_meta: f_norm_eps = 0.0e+00
| llm_load_print_meta: f_norm_rms_eps = 1.0e-05
| llm_load_print_meta: n_ff = 14336
| llm_load_print_meta: freq_base = 10000.0
| llm_load_print_meta: freq_scale = 1
| llm_load_print_meta: model type = 7B
| llm_load_print_meta: model ftype = mostly Q3_K - Medium
| llm_load_print_meta: model params = 46.70 B
| llm_load_print_meta: model size = 18.96 GiB (3.49 BPW)
| llm_load_print_meta: general.name = mistralai_mixtral-8x7b-v0.1
| llm_load_print_meta: BOS token = 1 ''
| llm_load_print_meta: EOS token = 2 ''
| llm_load_print_meta: UNK token = 0 ''
| llm_load_print_meta: PAD token = 0 ''
| llm_load_print_meta: LF token = 13 '<0x0A>'
| llm_load_tensors: ggml ctx size = 0.32 MB
| llm_load_tensors: using CUDA for GPU acceleration
| error loading model: create_tensor: tensor 'blk.0.ffn_gate.weight' not found
| llama_load_model_from_file: failed to load model
| 2024-01-20 04:40:58 UTC - Super AGI - ERROR - [/app/superagi/helper/llm_loader.py:27] -
| 2024-01-20 04:40:58 UTC - Super AGI - ERROR - [/app/superagi/controllers/models_controller.py:185] - Model not found.
| 2024-01-20 04:40:58 UTC - Super AGI - INFO - [/app/superagi/controllers/models_controller.py:203] - Error:
| 2024-01-20 04:40:58 UTC - Super AGI - INFO - [/app/superagi/controllers/models_controller.py:203] -
| INFO: 172.19.0.7:45274 - "GET /models_controller/test_local_llm HTTP/1.0" 404 Not Found

is might be the cpp version the problem: https://github.com/abetlen/llama-cpp-python/releases the latest is 0.2.31 not like in SuperAGI 2.7

alfi4000 · 2024-01-20T04:43:45Z

here is a screenshot of Nvidia it appeared after I clicked test!:

alfi4000 · 2024-01-20T04:56:18Z

Lol with this vicuna model it worked: https://huggingface.co/TheBloke/vicuna-13B-v1.5-GGUF

shiloh92 · 2024-01-29T02:39:09Z

This is what I learned so far.... and nothing works. Good luck to anyone willing to carry the torch forward until someone gets it running on Windows....... See my dev comment below.

Windows Setup:

Open config.yaml
Add '#' to line 12
Remove '#' on line 13, save the file and close.
Download or move a Local LLM file of your choice to 'local_model_path' folder
Open docker-compose.yaml
Paste under line 16 and line 18:
- "./local_model_path/dolphin-2.6-mistral-7b.Q5_K_M.gguf:/app/local_model_path"
Save the file and close.
Open cmd.exe from start menu
Paste and hit ENTER:

docker compose -f docker-compose-gpu.yml up --build

---- EXAMPLE of docker-compose.yaml ---- (example from 1/28/24 for Windows 11):

version: '3.8'
services:
backend:
volumes:
- "./:/app"
- "./local_model_path/dolphin-2.6-mistral-7b.Q5_K_M.gguf:/app/local_model_path"
build: .
depends_on:
- super__redis
- super__postgres
networks:
- super_network
command: ["/app/wait-for-it.sh", "super__postgres:5432","-t","60","--","/app/entrypoint.sh"]
celery:
volumes:
- "./:/app"
- "./local_model_path/dolphin-2.6-mistral-7b.Q5_K_M.gguf:/app/local_model_path"
- "${EXTERNAL_RESOURCE_DIR:-./workspace}:/app/ext"

I seriously recommend an easier way to VIEW local models within the Add Models tab (populate it from the local_model_path dir!! Even if unsupported, it should list them in the drop down. The TEST button errors out for me, so I spent 2 hours attempting to debug but this is ridiculous. One last attempt will be to try a third llm...

shiloh92 · 2024-01-29T02:48:55Z

models_controller.py:203 Error:

It indicates that there's an error in the models_controller.py file at line 203.
The error is a 404 Not Found for a GET request to /models_controller/test_local_llm.
The request seems to come from IP 172.18.0.7:39800, and it's being proxied at http://localhost:3000/.

rounak610 · 2024-01-29T04:42:36Z

@shiloh92 you need to add the model path in the docker-compose-gpu.yml file, not in the docker-compose.yaml file
after this you can use: docker compose -f docker-compose-gpu.yml up --build
you can refer this video for set-up

coder5492 added the question Further information is requested label Oct 2, 2023

rounak610 closed this as completed Jan 30, 2024

Trying to use this with local llms but there is no easy way to figure it out. #1295

Trying to use this with local llms but there is no easy way to figure it out. #1295

Comments

dreemur99 commented Sep 29, 2023 • edited Loading

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docker-compose.yaml

Dockerfile :

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alfi4000 commented Jan 17, 2024

volumes:

- ./gui:/app

- /app/node_modules/

- /app/.next/

uncomment to expose redis port to host

ports:

- "6379:6379"

uncomment to expose postgres port to host

ports:

- "5432:5432"

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