Instructions to use bynn-intelligence-com/decisionnode-edge-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bynn-intelligence-com/decisionnode-edge-mini with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="bynn-intelligence-com/decisionnode-edge-mini")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("bynn-intelligence-com/decisionnode-edge-mini")
model = AutoModelForMultimodalLM.from_pretrained("bynn-intelligence-com/decisionnode-edge-mini", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use bynn-intelligence-com/decisionnode-edge-mini 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 bynn-intelligence-com/decisionnode-edge-mini:Q8_0
# Run inference directly in the terminal:
llama cli -hf bynn-intelligence-com/decisionnode-edge-mini:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf bynn-intelligence-com/decisionnode-edge-mini:Q8_0
# Run inference directly in the terminal:
llama cli -hf bynn-intelligence-com/decisionnode-edge-mini: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 bynn-intelligence-com/decisionnode-edge-mini:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf bynn-intelligence-com/decisionnode-edge-mini: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 bynn-intelligence-com/decisionnode-edge-mini:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf bynn-intelligence-com/decisionnode-edge-mini:Q8_0

Use Docker

docker model run hf.co/bynn-intelligence-com/decisionnode-edge-mini:Q8_0

Llama new
LM Studio
Jan

vLLM

How to use bynn-intelligence-com/decisionnode-edge-mini with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/bynn-intelligence-com/decisionnode-edge-mini:Q8_0

SGLang

How to use bynn-intelligence-com/decisionnode-edge-mini with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "bynn-intelligence-com/decisionnode-edge-mini" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bynn-intelligence-com/decisionnode-edge-mini",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "bynn-intelligence-com/decisionnode-edge-mini" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bynn-intelligence-com/decisionnode-edge-mini",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use bynn-intelligence-com/decisionnode-edge-mini with Ollama:
```
ollama run hf.co/bynn-intelligence-com/decisionnode-edge-mini:Q8_0
```
Unsloth Desktop
Docker Model Runner
How to use bynn-intelligence-com/decisionnode-edge-mini with Docker Model Runner:
```
docker model run hf.co/bynn-intelligence-com/decisionnode-edge-mini:Q8_0
```

Lemonade

How to use bynn-intelligence-com/decisionnode-edge-mini with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull bynn-intelligence-com/decisionnode-edge-mini:Q8_0

Run and chat with the model

lemonade run user.decisionnode-edge-mini-Q8_0

List all available models

lemonade list

Atomic Chat

decisionnode-edge-mini / calibration.json

bynn-intelligence

DecisionNode Edge Mini 0.9.1

47dda17 verified 5 days ago

Raw History Blame Contribute Delete

381 Bytes

{
  "format": "decisionnode-edge-calibration-1",
  "text": {
    "choice": {
      "t0": 1.2505374542160104,
      "t1": 0.0,
      "k_min": 2,
      "k_max": 174
    },
    "truth": {
      "temperature": 1.4434581905599821,
      "bias": -0.029086327876874197
    },
    "score": {
      "t0": 1.0,
      "t1": 0.0,
      "k_min": 3,
      "k_max": 10
    }
  },
  "image": {}
}

	{
	"format": "decisionnode-edge-calibration-1",
	"text": {
	"choice": {
	"t0": 1.2505374542160104,
	"t1": 0.0,
	"k_min": 2,
	"k_max": 174
	},
	"truth": {
	"temperature": 1.4434581905599821,
	"bias": -0.029086327876874197
	},
	"score": {
	"t0": 1.0,
	"t1": 0.0,
	"k_min": 3,
	"k_max": 10
	}
	},
	"image": {}
	}