90 lines
2.7 KiB
Markdown
90 lines
2.7 KiB
Markdown
# How to Run Distributed Llama on 💻 Linux, MacOS or Windows
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This article describes how to run Distributed Llama on 4 devices, but you can also run it on 1, 2, 4, 8... devices. Please adjust the commands and topology according to your configuration.
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````
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[🔀 SWITCH OR ROUTER]
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| | | |
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| | | |_______ 🔸 device1 (ROOT) 10.0.0.1
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| | |_________ 🔹 device2 (WORKER 1) 10.0.0.2:9999
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| |___________ 🔹 device3 (WORKER 2) 10.0.0.3:9999
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|_____________ 🔹 device4 (WORKER 3) 10.0.0.4:9999
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````
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1. Install Git and C++ compiler on **🔸🔹 ALL** devices:
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* Linux:
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```
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sudo apt install git build-essential
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```
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* MacOS
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```
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brew install git
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```
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* Windows
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Install Git and Mingw (via [Chocolatey](https://chocolatey.org/install)):
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```powershell
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choco install git mingw
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```
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2. Connect **🔸🔹 ALL** devices to your **🔀 SWITCH OR ROUTER** via Ethernet cable. If you're using only two devices, it's better to connect them directly without a switch.
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3. Clone this repository and compile Distributed Llama on **🔸🔹 ALL** devices:
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```sh
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git clone https://github.com/b4rtaz/distributed-llama.git
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cd distributed-llama
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make dllama
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make dllama-api
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```
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4. Download the model to the **🔸 ROOT** device using the `launch.py` script. You don't need to download the model on worker devices.
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```sh
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python3 launch.py # Prints a list of available models
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python3 launch.py llama3_2_3b_instruct_q40 # Downloads the model to the root device
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```
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5. Start workers on all **🔹 WORKER** devices:
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```sh
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./dllama worker --port 9999 --nthreads 4
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```
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6. Run the inference to test if everything works fine on the **🔸 ROOT** device:
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```sh
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./dllama inference \
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--prompt "Hello world" \
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--steps 32 \
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--model models/llama3_2_3b_instruct_q40/dllama_model_llama3_2_3b_instruct_q40.m \
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--tokenizer models/llama3_2_3b_instruct_q40/dllama_tokenizer_llama3_2_3b_instruct_q40.t \
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--buffer-float-type q80 \
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--nthreads 4 \
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--max-seq-len 4096 \
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--workers 10.0.0.2:9999 10.0.0.3:9999 10.0.0.4:9999
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```
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7. To run the API server, start it on the **🔸 ROOT** device:
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```sh
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./dllama-api \
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--port 9999 \
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--model models/llama3_2_3b_instruct_q40/dllama_model_llama3_2_3b_instruct_q40.m \
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--tokenizer models/llama3_2_3b_instruct_q40/dllama_tokenizer_llama3_2_3b_instruct_q40.t \
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--buffer-float-type q80 \
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--nthreads 4 \
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--max-seq-len 4096 \
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--workers 10.0.0.2:9999 10.0.0.3:9999 10.0.0.4:9999
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```
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Now you can connect to the API server:
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```
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http://10.0.0.1:9999/v1/models
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```
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8. When the API server is running, you can open the web chat in your browser, open [llama-ui.js.org](https://llama-ui.js.org/), go to the settings and set the base URL to: `http://10.0.0.1:9999`. Press the "save" button and start chatting!
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