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
llama-cpp-K2-FAST2 / tools /ui /src /lib /components /app /chat /ChatScreen /ChatScreenGreeting.svelte
Download tools/ui/src/lib/components/app/chat/ChatScreen/ChatScreenGreeting.svelte from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 594 Bytes
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/src/lib/components/app/chat/ChatScreen/ChatScreenGreeting.svelte
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/tools/ui/src/lib/components/app/chat/ChatScreen/ChatScreenGreeting.svelte
-
curl -L -o ChatScreenGreeting.svelte https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/src/lib/components/app/chat/ChatScreen/ChatScreenGreeting.svelte
594 Bytes
| <script lang="ts"> | |
| import { serverStore } from '$lib/stores'; | |
| interface Props { | |
| isEmpty: boolean; | |
| } | |
| let { isEmpty = false }: Props = $props(); | |
| </script> | |
| <div | |
| class={[ | |
| 'pointer-events-none mb-4 hidden px-4 text-center text-balance', | |
| isEmpty && 'mb-[calc(50dvh-8rem)] md:mb-8 pointer-events-auto block!' | |
| ]} | |
| > | |
| <h1 class="mb-2 text-2xl font-semibold tracking-tight md:text-3xl">Hello there</h1> | |
| <p class="text-muted-foreground md:text-lg"> | |
| {serverStore.props?.modalities?.audio ? 'Record audio, type a message ' : 'Type a message'} or upload | |
| files to get started | |
| </p> | |
| </div> | |