Instructions to use dkudos/cinimod-devops with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use dkudos/cinimod-devops with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf dkudos/cinimod-devops:Q8_0
# Run inference directly in the terminal:
llama cli -hf dkudos/cinimod-devops:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf dkudos/cinimod-devops:Q8_0
# Run inference directly in the terminal:
llama cli -hf dkudos/cinimod-devops:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf dkudos/cinimod-devops:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf dkudos/cinimod-devops:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf dkudos/cinimod-devops:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf dkudos/cinimod-devops:Q8_0

Use Docker

docker model run hf.co/dkudos/cinimod-devops:Q8_0

LM Studio
Jan

vLLM

How to use dkudos/cinimod-devops with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dkudos/cinimod-devops"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dkudos/cinimod-devops",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/dkudos/cinimod-devops:Q8_0

Ollama
How to use dkudos/cinimod-devops with Ollama:
```
ollama run hf.co/dkudos/cinimod-devops:Q8_0
```
Unsloth Desktop
Docker Model Runner
How to use dkudos/cinimod-devops with Docker Model Runner:
```
docker model run hf.co/dkudos/cinimod-devops:Q8_0
```

Lemonade

How to use dkudos/cinimod-devops with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull dkudos/cinimod-devops:Q8_0

Run and chat with the model

lemonade run user.cinimod-devops-Q8_0

List all available models

lemonade list

Atomic Chat

dkudos commited on Sep 15

Commit

cb6abf3

verified ·

1 Parent(s): ad7c8c2

Update README.md

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@@ -14,7 +14,7 @@ model-index:
   - name: Cinimod DevOps 300M
     results: []
 ---
 # Cinimod DevOps 300M
 A 287M-parameter decoder-only causal language model (Llama-3 style architecture), trained from scratch on a DevOps/ops SysAdmin domain corpus. Target usage: devops tooling assistance, ops documentation, and small on-box language modeling.

   - name: Cinimod DevOps 300M
     results: []
 ---
+# The Model is ONLY PRE-TRAINED ATM
 # Cinimod DevOps 300M
 A 287M-parameter decoder-only causal language model (Llama-3 style architecture), trained from scratch on a DevOps/ops SysAdmin domain corpus. Target usage: devops tooling assistance, ops documentation, and small on-box language modeling.