History

Gary Mulder ed19071ef8 Renamed and moved old Dockerfiles		2023-05-23 19:38:37 +00:00
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Dockerfile	Initial commit of auto docker	2023-05-23 19:26:40 +00:00
Dockerfile.cuda_simple	Renamed and moved old Dockerfiles	2023-05-23 19:38:37 +00:00
Dockerfile.openblas_simple	Renamed and moved old Dockerfiles	2023-05-23 19:38:37 +00:00
hug_model.py	Initial commit of auto docker	2023-05-23 19:26:40 +00:00
README.md	Update README.md	2023-05-23 20:36:21 +01:00
start_server.sh	Initial commit of auto docker	2023-05-23 19:26:40 +00:00

README.md

Get model from Hugging Face

python3 ./hug_model.py

You should now have a model in the current directory and model.bin symlinked to it for the subsequent Docker build and copy step. e.g.

docker $ ls -lh *.bin
-rw-rw-r-- 1 user user 4.8G May 23 18:30 <downloaded-model-file>.q5_1.bin
lrwxrwxrwx 1 user user   24 May 23 18:30 model.bin -> <downloaded-model-file>.q5_1.bin

Note #1: Make sure you have enough disk space to d/l the model. As the model is then copied into the image you will need at least TWICE as much disk space as the size of the model:

Model	Quantized size
7B	5 GB
13B	10 GB
30B	25 GB
65B	50 GB

Note #2: If you want to pass or tune additional parameters, customise ./start_server.sh before running docker build ...

Install Docker Server

Note #3: This was tested with Docker running on Linux. If you can get it working on Windows or MacOS, please update this README with a PR!

Install Docker Engine

Use OpenBLAS

No NVidia GPU, defaults to python:3-slim-bullseye Docker base image and OpenBlAS:

Build:

docker build --build-arg -t openblas .

Run:

docker run --cap-add SYS_RESOURCE -t openblas

Use CuBLAS

Requires NVidia GPU and Docker NVidia support (see container-toolkit/install-guide)

Build:

docker build --build-arg IMAGE=nvidia/cuda:12.1.1-devel-ubuntu22.04 -t opencuda .

Run:

docker run --cap-add SYS_RESOURCE -t cublas