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/utils/get-datetime.ts from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 1.4 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/src/lib/utils/get-datetime.ts
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/tools/ui/src/lib/utils/get-datetime.ts
-
curl -L -o get-datetime.ts https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/src/lib/utils/get-datetime.ts
1.4 kB
| /** | |
| * Browser executor for the `get_datetime` tool. It runs in the browser, so it | |
| * reports the user's own clock and time zone instead of the server's UTC time - | |
| * a chat about "tomorrow" means the user's tomorrow, not the host's. | |
| * | |
| * @see buildGetDatetimeToolDefinition in constants/get-datetime.ts - tool schema sent to the LLM | |
| */ | |
| import type { ToolExecutionResult } from '$lib/types'; | |
| function pad(value: number): string { | |
| return String(value).padStart(2, '0'); | |
| } | |
| /** ISO 8601 in local time, e.g. `2026-08-17T14:05:09+02:00` */ | |
| function localIsoString(date: Date): string { | |
| // getTimezoneOffset() counts minutes behind UTC, ISO 8601 counts them ahead | |
| const offset = -date.getTimezoneOffset(); | |
| const sign = offset < 0 ? '-' : '+'; | |
| const absOffset = Math.abs(offset); | |
| const day = `${date.getFullYear()}-${pad(date.getMonth() + 1)}-${pad(date.getDate())}`; | |
| const time = `${pad(date.getHours())}:${pad(date.getMinutes())}:${pad(date.getSeconds())}`; | |
| return `${day}T${time}${sign}${pad(Math.floor(absOffset / 60))}:${pad(absOffset % 60)}`; | |
| } | |
| /** The `result` field keeps the shape the `get_datetime` renderer already reads. */ | |
| export function executeGetDatetimeTool(): ToolExecutionResult { | |
| const now = new Date(); | |
| return { | |
| content: JSON.stringify({ | |
| result: localIsoString(now), | |
| timezone: Intl.DateTimeFormat().resolvedOptions().timeZone | |
| }), | |
| isError: false | |
| }; | |
| } | |