All apps · 0 apps
OpenChat-Cuda
Docker app from el_pino's Repository
Overview
Readme
View on GitHub
A self-hosted, offline, ChatGPT-like chatbot with different LLM support. 100% private, with no data leaving your device.
How to install
Install OpenLLM anywhere else with Docker
You can run OpenLLM on any x86 system. Make sure you have Docker installed.
Then, clone this repo and cd into it:
git clone https://github.com/edgar971/open-chat.git
cd open-chat
You can now run OpenLLM with any of the following models depending upon your hardware:
| Model size | Model used | Minimum RAM required | How to start OpenLLM |
|---|---|---|---|
| 7B | Nous Hermes Llama 2 7B (GGML q4_0) | 8GB | docker compose up -d |
| 13B | Nous Hermes Llama 2 13B (GGML q4_0) | 16GB | docker compose -f docker-compose-13b.yml up -d |
| 70B | Meta Llama 2 70B Chat (GGML q4_0) | 48GB | docker compose -f docker-compose-70b.yml up -d |
You can access OpenLLM at http://localhost:3000.
To stop OpenLLM, run:
docker compose down
API Configuration
Additional settings can be found here and added as env variables or arguments to the run.sh (--n_ctx 12) script.
Example:
version: '3'
services:
api:
image: ghcr.io/edgar971/open-chat-cuda:latest
environment:
- MODEL=/path/to/your/model
- N_CTX=4096
ports:
Acknowledgements
A massive thank you to the following developers and teams for making OpenLLM possible:
- Mckay Wrigley for building Chatbot UI.
- Georgi Gerganov for implementing llama.cpp.
- Andrei for building the Python bindings for llama.cpp.
- NousResearch for fine-tuning the Llama 2 7B and 13B models.
- Tom Jobbins for quantizing the Llama 2 models.
- Meta for releasing Llama 2 under a permissive license.
Install OpenChat-Cuda on Unraid in a few clicks.
Find OpenChat-Cuda in Community Apps on your Unraid server, review the template, and click Install. Unraid handles the Docker app or plugin setup from the published template.
Related apps
Explore more like this
Explore allDetails
ghcr.io/edgar971/open-chat-cuda:v1.0.6Runtime arguments
- Web UI
http://[IP]:[PORT:3000]/- Network
bridge- Shell
sh- Privileged
- false
- Extra Params
--gpus all
Template configuration
The local model path
- Target
- MODEL
- Default
- /models/llama-2-7b-chat.bin
GGML Model Binary.
- Target
- MODEL_DOWNLOAD_URL
- Default
- https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/resolve/main/llama-2-7b-chat.ggmlv3.q4_0.bin
The local model directory to use as a cache
- Target
- /models
- Default
- /mnt/user/appdata/models
Chat UI Port
- Target
- 3000
- Default
- 3000
HTTP API Port
- Target
- 8000
- Default
- 8000
Layers to offload to GPU. Update this number if server fails to load.
- Target
- N_GPU_LAYERS
- Value
- 12