Instructions to use botbottingbot/Modular_Intelligence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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
```

Modular_Intelligence / .gitignore

botbottingbot

Create .gitignore

205980f verified 7 months ago

Raw

History Blame Contribute Delete

1.95 kB

	# ==========================================
	# Python
	# ==========================================
	__pycache__/
	*.pyc
	*.pyo
	*.pyd
	*.pdb
	*.pkl
	*.egg-info/
	*.eggs/
	*.so

	# Virtual environments
	venv/
	.env/
	ENV/
	env/
	.venv/

	# Jupyter
	.ipynb_checkpoints/
	*.ipynb

	# ==========================================
	# HuggingFace Spaces
	# ==========================================
	# HF build artifacts
	hf_home/
	hf_cache/
	huggingface/
	.local-huggingface/
	*.lock

	# Spaces autosave artifacts
	spaces-assets/
	frontend/node_modules/
	app_files/
	logs/

	# Do not commit model weights unless intentional
	*.bin
	*.pt
	*.pth
	*.safetensors
	*.onnx

	# ==========================================
	# System / OS files
	# ==========================================
	.DS_Store
	Thumbs.db
	desktop.ini

	# ==========================================
	# Environment & Secrets
	# ==========================================
	*.env
	*.key
	*.pem
	secret*
	config/
	credentials.json
	token*
	auth*

	# ==========================================
	# Node (HF frontend builds)
	# ==========================================
	node_modules/
	npm-debug.log
	yarn-debug.log
	yarn-error.log

	# ==========================================
	# Python packaging
	# ==========================================
	build/
	dist/
	*.egg
	*.manifest

	# ==========================================
	# Compiled code
	# ==========================================
	*.class
	*.o
	*.a
	*.out

	# ==========================================
	# Logs
	# ==========================================
	*.log
	logs/
	*.stackdump

	# ==========================================
	# Temporary files
	# ==========================================
	*.tmp
	*.temp
	tmp/
	temp/
	*.bak
	*~
	.cache/
	.mypy_cache/
	.pytest_cache/

	# ==========================================
	# VSCode / Editor
	# ==========================================
	.vscode/
	.idea/
	*.swp
	*.swo

	# ==========================================
	# Git
	# ==========================================
	.gitignore~
	.gitattributes~