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LLM API

There are many API we can use. For the original SSBSE 2023 paper, we utilised Python3 API for GPT 3.5.

There are some other options, documented below.

OLLAMA API

You can download any hugging face model or use ollama ready to use models. https://ollama.ai and https://hub.docker.com/r/ollama/ollama.

Install ollama:

curl https://ollama.ai/install.sh | sh

Check the the version of ollama:

ollama --version

ollama models

To pull ready-to-user from ollama DB:

nano model2
[copy then this text into the file]
FROM phind-codellama:latest
PARAMETER num_gpu 0
[save and exit]

ollama create ollama_phi_no-gpu -f model2

You can find all the models here: https://ollama.ai/library.

To run and use the model in an interactive way:

ollama run ollama_phi_no-gpu:latest

or as a query to use inside other programs:

ollama run ollama_phi_no-gpu:latest "Give me a short C program only. The code gets to numbers and return the sum of these"

or

ollama run ollama_phi_no-gpu:latest "Give me a short C program only. The code gets to numbers and return the sum of these" > resultx.txt

Hagging face model and other external models

To use your own or hagging face model:

nano model1
[copy then this text into the file]
FROM ./MODELS/deepseek-coder-6.7b-instruct.Q5_K_M.gguf
PARAMETER num_gpu 0
[save and exit]

ollama create deepseek_no-gpu -f model1
ollama run deepseek_no-gpu

Say we pull earlier the model, for example:

cd MODELS/
wget https://huggingface.co/TheBloke/deepseek-coder-6.7B-instruct-GGUF/resolve/main/deepseek-coder-6.7b-instruct.Q5_K_M.gguf
cd ..

To see all models loaded to ollama API:

ollama list

and we get (for example) this output:

NAME                        	ID          	SIZE  	MODIFIED           
deepseek_coder_no-gpu:latest	e2b8aad670cd	4.8 GB	6 seconds ago     	
ollama_phi_no-gpu:latest    	254aa43a6301	19 GB 	About a minute ago	
phind-codellama:latest      	566e1b629c44	19 GB 	About a minute ago