Instructions to use isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp 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 isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K # Run inference directly in the terminal: llama cli -hf isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K # Run inference directly in the terminal: llama cli -hf isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K
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 isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K # Run inference directly in the terminal: ./llama-cli -hf isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K
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 isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K
Use Docker
docker model run hf.co/isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K
- LM Studio
- Jan
- Ollama
How to use isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp with Ollama:
ollama run hf.co/isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K
- Unsloth Desktop
- Docker Model Runner
How to use isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp with Docker Model Runner:
docker model run hf.co/isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K
- Lemonade
How to use isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp:Q2_K
Run and chat with the model
lemonade run user.wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp-Q2_K
List all available models
lemonade list
- Atomic Chat
Download stable-diffusion-cpp-nvidia/ggml/src/CMakeFiles/ggml-cpu.dir/ggml-cpu/ops.cpp.o from isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp: direct link, hf CLI and curl.
- Browser
- Download file 330 kB
-
https://huggingface.co/isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp/resolve/main/stable-diffusion-cpp-nvidia/ggml/src/CMakeFiles/ggml-cpu.dir/ggml-cpu/ops.cpp.o
- Command line
-
hf download hf://isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp/stable-diffusion-cpp-nvidia/ggml/src/CMakeFiles/ggml-cpu.dir/ggml-cpu/ops.cpp.o
-
curl -L -o ops.cpp.o https://huggingface.co/isfs/wan-2.2-5b-ti2v-gguf-stable-diffusion-cpp/resolve/main/stable-diffusion-cpp-nvidia/ggml/src/CMakeFiles/ggml-cpu.dir/ggml-cpu/ops.cpp.o
330 kB
- Xet hash:
- 8db62599cda37f5182278680730c77cebc0dd0fedf083cb9c816ed471d383b34
- Size of remote file:
- 330 kB
- SHA256:
- 3c164e81c0d3c9f6386c9445b8d33fd17cc691b44e1c0c65e9d8780edf5c8a2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.