Instructions to use MidnightRunner/Misc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use MidnightRunner/Misc with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="MidnightRunner/Misc", filename="Qwen2.5-VL-7B-Instruct-Q3_K_S.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 MidnightRunner/Misc with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf MidnightRunner/Misc:UD-Q4_K_S # Run inference directly in the terminal: llama-cli -hf MidnightRunner/Misc:UD-Q4_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf MidnightRunner/Misc:UD-Q4_K_S # Run inference directly in the terminal: llama-cli -hf MidnightRunner/Misc:UD-Q4_K_S
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 MidnightRunner/Misc:UD-Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf MidnightRunner/Misc:UD-Q4_K_S
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 MidnightRunner/Misc:UD-Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf MidnightRunner/Misc:UD-Q4_K_S
Use Docker
docker model run hf.co/MidnightRunner/Misc:UD-Q4_K_S
- LM Studio
- Jan
- Ollama
How to use MidnightRunner/Misc with Ollama:
ollama run hf.co/MidnightRunner/Misc:UD-Q4_K_S
- Unsloth Studio new
How to use MidnightRunner/Misc 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 MidnightRunner/Misc 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 MidnightRunner/Misc to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MidnightRunner/Misc to start chatting
- Docker Model Runner
How to use MidnightRunner/Misc with Docker Model Runner:
docker model run hf.co/MidnightRunner/Misc:UD-Q4_K_S
- Lemonade
How to use MidnightRunner/Misc with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MidnightRunner/Misc:UD-Q4_K_S
Run and chat with the model
lemonade run user.Misc-UD-Q4_K_S
List all available models
lemonade list
Upload 6 files
Browse files- .gitattributes +6 -0
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- Wan2.2-I2V-A14B-4steps-lora-rank64-Seko-V1_low_noise_model.safetensors +3 -0
- Wan2.2-Lightning_I2V-A14B-4steps-lora_HIGH_fp16.safetensors +3 -0
- Wan2.2-Lightning_I2V-A14B-4steps-lora_LOW_fp16.safetensors +3 -0
- Wan21_I2V_14B_lightx2v_cfg_step_distill_lora_rank64.safetensors +3 -0
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