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/components/app/misc/TruncatedText.svelte from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 1.07 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/src/lib/components/app/misc/TruncatedText.svelte
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/tools/ui/src/lib/components/app/misc/TruncatedText.svelte
-
curl -L -o TruncatedText.svelte https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/src/lib/components/app/misc/TruncatedText.svelte
1.07 kB
| <script lang="ts"> | |
| import * as Tooltip from '$lib/components/ui/tooltip'; | |
| interface Props { | |
| text: string; | |
| class?: string; | |
| showTooltip?: boolean; | |
| } | |
| let { class: className = '', showTooltip = true, text }: Props = $props(); | |
| let textElement: HTMLSpanElement | undefined = $state(); | |
| let isTruncated = $state(false); | |
| function checkTruncation() { | |
| if (textElement) { | |
| isTruncated = textElement.scrollWidth > textElement.clientWidth; | |
| } | |
| } | |
| $effect(() => { | |
| if (textElement) { | |
| checkTruncation(); | |
| const observer = new ResizeObserver(checkTruncation); | |
| observer.observe(textElement); | |
| return () => observer.disconnect(); | |
| } | |
| }); | |
| </script> | |
| {#if isTruncated && showTooltip} | |
| <Tooltip.Root> | |
| <Tooltip.Trigger class="{className} min-w-0"> | |
| <span bind:this={textElement} class="block truncate"> | |
| {text} | |
| </span> | |
| </Tooltip.Trigger> | |
| <Tooltip.Content class="z-[9999]"> | |
| <p>{text}</p> | |
| </Tooltip.Content> | |
| </Tooltip.Root> | |
| {:else} | |
| <span bind:this={textElement} class="{className} block min-w-0 truncate"> | |
| {text} | |
| </span> | |
| {/if} | |