Instructions to use K00B404/CognitiveDollhouseModels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use K00B404/CognitiveDollhouseModels with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="K00B404/CognitiveDollhouseModels", filename="DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored-IQ3_XS.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use K00B404/CognitiveDollhouseModels with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf K00B404/CognitiveDollhouseModels:IQ3_XS # Run inference directly in the terminal: llama-cli -hf K00B404/CognitiveDollhouseModels:IQ3_XS
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf K00B404/CognitiveDollhouseModels:IQ3_XS # Run inference directly in the terminal: llama-cli -hf K00B404/CognitiveDollhouseModels:IQ3_XS
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 K00B404/CognitiveDollhouseModels:IQ3_XS # Run inference directly in the terminal: ./llama-cli -hf K00B404/CognitiveDollhouseModels:IQ3_XS
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 K00B404/CognitiveDollhouseModels:IQ3_XS # Run inference directly in the terminal: ./build/bin/llama-cli -hf K00B404/CognitiveDollhouseModels:IQ3_XS
Use Docker
docker model run hf.co/K00B404/CognitiveDollhouseModels:IQ3_XS
- LM Studio
- Jan
- Ollama
How to use K00B404/CognitiveDollhouseModels with Ollama:
ollama run hf.co/K00B404/CognitiveDollhouseModels:IQ3_XS
- Unsloth Studio new
How to use K00B404/CognitiveDollhouseModels with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for K00B404/CognitiveDollhouseModels to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for K00B404/CognitiveDollhouseModels to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for K00B404/CognitiveDollhouseModels to start chatting
- Docker Model Runner
How to use K00B404/CognitiveDollhouseModels with Docker Model Runner:
docker model run hf.co/K00B404/CognitiveDollhouseModels:IQ3_XS
- Lemonade
How to use K00B404/CognitiveDollhouseModels with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull K00B404/CognitiveDollhouseModels:IQ3_XS
Run and chat with the model
lemonade run user.CognitiveDollhouseModels-IQ3_XS
List all available models
lemonade list
baseline model set for CognitiveDollhouse POC
Browse files- DWPose/dw-ll_ucoco_384.onnx +3 -0
- DWPose/yolox_l.onnx +3 -0
- Justin_Interior_plan_V150.safetensors +3 -0
- add_detail.safetensors +3 -0
- buildings_view_from_indoors-000009.safetensors +3 -0
- ip-adapter-faceid-plus_sd15_lora.safetensors +3 -0
- ip-adapter-plus-face_sd15.safetensors +3 -0
- ip-adapter_sd15.safetensors +3 -0
- ip-adapter_sd15_light_v11.bin +3 -0
- lora_garden_architecture_Exterior_SDlife_Chiasedamme_V1_0.safetensors +3 -0
- warehouse_1nt3r10r-p.safetensors +3 -0
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