Instructions to use botbottingbot/Modular_Intelligence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use botbottingbot/Modular_Intelligence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="botbottingbot/Modular_Intelligence")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("botbottingbot/Modular_Intelligence", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use botbottingbot/Modular_Intelligence with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "botbottingbot/Modular_Intelligence" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "botbottingbot/Modular_Intelligence", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/botbottingbot/Modular_Intelligence
- SGLang
How to use botbottingbot/Modular_Intelligence 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 "botbottingbot/Modular_Intelligence" \ --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": "botbottingbot/Modular_Intelligence", "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 "botbottingbot/Modular_Intelligence" \ --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": "botbottingbot/Modular_Intelligence", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use botbottingbot/Modular_Intelligence with Docker Model Runner:
docker model run hf.co/botbottingbot/Modular_Intelligence
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## Modular Intelligence Demo
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A universal, domain-agnostic framework for structured reasoning:
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### Modules
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- Analysis Note
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- Document Explainer
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- Strategy Memo
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- Message/Post Reply
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- Profile/Application Draft
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- System Blueprint
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- Modular Brainstorm
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### Checkers
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Every key module has a paired checker:
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- reasoning
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- structure
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- clarity
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- alignment
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- missing elements
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### Purpose
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To demonstrate how AI outputs become **stable, modular, and verifiable** through a structured architecture.
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### How to use
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1. Select a module
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2. Fill the inputs
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3. Run
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4. (Optional) Run the checker
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### Extending
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- Add custom modules
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- Plug in any open-source model
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- Deploy as API
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