Image-Text-to-Text
Transformers
Safetensors
GGUF
qwen3_5
system-one
decision-making
classification
calibration
structured-output
on-device
multimodal
Instructions to use bynn-intelligence-com/decisionnode-edge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bynn-intelligence-com/decisionnode-edge 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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("bynn-intelligence-com/decisionnode-edge") model = AutoModelForMultimodalLM.from_pretrained("bynn-intelligence-com/decisionnode-edge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use bynn-intelligence-com/decisionnode-edge 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:Q8_0 # Run inference directly in the terminal: llama cli -hf bynn-intelligence-com/decisionnode-edge: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:Q8_0 # Run inference directly in the terminal: llama cli -hf bynn-intelligence-com/decisionnode-edge: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:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf bynn-intelligence-com/decisionnode-edge: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:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf bynn-intelligence-com/decisionnode-edge:Q8_0
Use Docker
docker model run hf.co/bynn-intelligence-com/decisionnode-edge:Q8_0
- Llama new
- LM Studio
- Jan
- vLLM
How to use bynn-intelligence-com/decisionnode-edge 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" # 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", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bynn-intelligence-com/decisionnode-edge:Q8_0
- SGLang
How to use bynn-intelligence-com/decisionnode-edge 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" \ --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", "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" \ --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", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use bynn-intelligence-com/decisionnode-edge with Ollama:
ollama run hf.co/bynn-intelligence-com/decisionnode-edge:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use bynn-intelligence-com/decisionnode-edge with Docker Model Runner:
docker model run hf.co/bynn-intelligence-com/decisionnode-edge:Q8_0
- Lemonade
How to use bynn-intelligence-com/decisionnode-edge with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bynn-intelligence-com/decisionnode-edge:Q8_0
Run and chat with the model
lemonade run user.decisionnode-edge-Q8_0
List all available models
lemonade list
- Atomic Chat
Download MANIFEST.sha256 from bynn-intelligence-com/decisionnode-edge: direct link, hf CLI and curl.
- Browser
- Download file 3.22 kB
-
https://huggingface.co/bynn-intelligence-com/decisionnode-edge/resolve/main/MANIFEST.sha256
- Command line
-
hf download hf://bynn-intelligence-com/decisionnode-edge/MANIFEST.sha256
-
curl -L -o MANIFEST.sha256 https://huggingface.co/bynn-intelligence-com/decisionnode-edge/resolve/main/MANIFEST.sha256
3.22 kB
| 0d96a4ff68ad6d4b6f1f30f713b18d5184912ba8dd389f86aa7710db079abcb0 ./LICENSE | |
| 50cbab8a892c5f2993b8c7351a99182507472def3b1374558308605d99b86b32 ./LICENSE-base | |
| 2014f13a6fe1d9178c84cde47bb087a7a74adbe38650f1823a944077081e86d0 ./LICENSING.md | |
| e4dcac398e39a098e07f625ed239949296a2000d95dcc275cb0d8083ebb51dc9 ./NOTICE | |
| 8e38c861ae8950a50cb8fc12d334cc5a10136bf7b2204c5661bc7a29e035ed94 ./README.md | |
| c44489690e63adb3abd8c65ede675fadc5714126e3f866cbd292df824880cb77 ./assets/decisionnode-banner.png | |
| 544b3d40cc9e355b16f8c131426c21245c1b5847a46c40c1b4be2c33a447b4fa ./box_calibration.json | |
| 5febf5c3cb5843034f2251d959c475a4a629dec65bf3ea494b4fed0a3b8aa3aa ./calibration.json | |
| 28b44a18f60b7e3039c503971b6d194b51c723f0c8a62d56bd6ce7f7f34e9f87 ./config.json | |
| 8da27e0c66f1196243e6a4220213050001be1837b502ba8b20bd4e787bb1091a ./decisionnode-edge-0.9.1-q8_0.gguf | |
| 420be98b7242ec41ede64a3b72a461c8af30ddebbe766f4d13c4b7183658fd60 ./decisionnode_edge.json | |
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| e0a87595ad939efa5585b61844d3a2a70d29ba7752f68b8139f2195753a6bfde ./examples/request.json | |
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| 0d96a4ff68ad6d4b6f1f30f713b18d5184912ba8dd389f86aa7710db079abcb0 ./runtime/LICENSE | |
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| e0a87595ad939efa5585b61844d3a2a70d29ba7752f68b8139f2195753a6bfde ./runtime/examples/request.json | |
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| 0c067d73ac9a01af3049c980c08f35acd257e4044372fd2066a74db466499a39 ./runtime/src/decisionnode_edge/__init__.py | |
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| 736741c822983f1d7d8ed26ea01227f2f2e902c98dc7d0c21d8fa5abcf219150 ./runtime/src/decisionnode_edge/answers.py | |
| 1488cd43642f6bd49b810683b7e72688e98dc62d2e955c202331e027a62b1889 ./runtime/src/decisionnode_edge/backends.py | |
| 4ace977690bb7ae16010a298c478f1a5056caaf724c0d696b5ddac6699225f6b ./runtime/src/decisionnode_edge/build.py | |
| 3e2d2198d9fd4fac076773e655a0c73c810a932be07ce99460edee64fb7004bc ./runtime/src/decisionnode_edge/model.py | |
| 3be9ac7eb2807241d0b9b49cb5797049395f7fbca6ddee9a645274edd1c3e4a5 ./runtime/src/decisionnode_edge/places.py | |
| fb1b35692c68ad904d44743f580e2145ff68d14ac7b94267c7c19402f88b2e5f ./runtime/src/decisionnode_edge/request.py | |
| bc5ebac62720ff5f0317ab757126eb25621af046da94cb7564ec41d482b277f2 ./runtime/src/decisionnode_edge/server.py | |
| 969e07b2698c7b746cf7e5c390c8110756053c2a6495a30d84a411d54a9054c6 ./runtime/src/decisionnode_edge/systemone.py | |
| 670afbb7b0fcc7f65f1c7d11f868a3daf143c2210eed0d528a27938d24c2327a ./runtime/src/decisionnode_edge/template.py | |
| 6e9f31870a35eb9372bbc8719603e5d02f2e07eff90af9f7b77fe3b17d3628ff ./tokenizer.json | |
| 429721f730f42043159445b48039714682fac2cef2ad0e82917dfa0c8ca5f430 ./tokenizer_config.json | |
| d039cd7d88b3502a99edd455496b75b44ecf7dd3b3669748bafac37e6cecc085 ./video_preprocessor_config.json | |