Instructions to use VladHong/llama-cpp-K2-FAST2 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 VladHong/llama-cpp-K2-FAST2 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 VladHong/llama-cpp-K2-FAST2 # Run inference directly in the terminal: llama cli -hf VladHong/llama-cpp-K2-FAST2
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf VladHong/llama-cpp-K2-FAST2 # Run inference directly in the terminal: llama cli -hf VladHong/llama-cpp-K2-FAST2
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf VladHong/llama-cpp-K2-FAST2 # Run inference directly in the terminal: ./build/bin/llama cli -hf VladHong/llama-cpp-K2-FAST2
Use Docker
docker model run hf.co/VladHong/llama-cpp-K2-FAST2
- Llama new
- LM Studio
- Jan
- Ollama
How to use VladHong/llama-cpp-K2-FAST2 with Ollama:
ollama run hf.co/VladHong/llama-cpp-K2-FAST2
- Unsloth Desktop
- Docker Model Runner
How to use VladHong/llama-cpp-K2-FAST2 with Docker Model Runner:
docker model run hf.co/VladHong/llama-cpp-K2-FAST2
- Lemonade
How to use VladHong/llama-cpp-K2-FAST2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull VladHong/llama-cpp-K2-FAST2
Run and chat with the model
lemonade run user.llama-cpp-K2-FAST2-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Download tools/ui/src/lib/constants/css-classes.constants.ts from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 1.21 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/src/lib/constants/css-classes.constants.ts
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/tools/ui/src/lib/constants/css-classes.constants.ts
-
curl -L -o css-classes.constants.ts https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/src/lib/constants/css-classes.constants.ts
1.21 kB
| export const BOX_BORDER = | |
| 'border border-border/30 focus-within:border-border dark:border-border/20 dark:focus-within:border-border'; | |
| export const INPUT_CLASSES = ` | |
| bg-muted/60 dark:bg-muted/75 | |
| ${BOX_BORDER} | |
| shadow-sm | |
| outline-none | |
| text-foreground | |
| `; | |
| export const PANEL_CLASSES = ` | |
| bg-background | |
| border border-border/30 dark:border-border/20 | |
| shadow-sm backdrop-blur-lg! | |
| rounded-t-lg! | |
| `; | |
| export const CHAT_FORM_POPOVER_MAX_HEIGHT = 'max-h-80'; | |
| export const DIALOG_SUBMENU_CONTENT = 'w-60'; | |
| /** Selects the focused chat-form input (either renderer) to restore focus after model actions. */ | |
| export const CHAT_INPUT_FOCUS_SELECTOR = | |
| '[data-slot="input-area"] textarea, [data-slot="input-area"] [contenteditable="true"]'; | |
| /** Default Tailwind size class for inline icon components (lucide, etc.). */ | |
| export const ICON_CLASS_DEFAULT = 'h-4 w-4'; | |
| /** Small Tailwind size class for inline icons. */ | |
| export const ICON_CLASS_SM = 'h-3.5 w-3.5'; | |
| /** Extra-small Tailwind size class for inline icons. */ | |
| export const ICON_CLASS_XS = 'h-3 w-3'; | |
| /** Icon size + spinning animation; used for live-streaming tool indicators. */ | |
| export const ICON_CLASS_SPIN = 'h-4 w-4 animate-spin'; | |