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/vitest-setup-client.ts from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 2.4 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/vitest-setup-client.ts
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/tools/ui/vitest-setup-client.ts
-
curl -L -o vitest-setup-client.ts https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/vitest-setup-client.ts
2.4 kB
| /// <reference types="@vitest/browser/matchers" /> | |
| /// <reference types="@vitest/browser/providers/playwright" /> | |
| import { beforeEach, vi } from 'vitest'; | |
| // Mock fetch for API calls during client tests. | |
| // In test environment there is no backend server, so we intercept | |
| // the specific endpoints the app uses and return valid mock data. | |
| // The passthrough target is captured once at module load: capturing it | |
| // inside beforeEach grabs the previous test's spy (vi.spyOn returns the | |
| // existing spy), making the default branch recurse on itself as soon as | |
| // a test fetches a URL outside the mocked set. | |
| const originalFetch = globalThis.fetch.bind(globalThis); | |
| beforeEach(() => { | |
| vi.spyOn(globalThis, 'fetch').mockImplementation( | |
| async (input: RequestInfo | URL, init?: RequestInit) => { | |
| const url = typeof input === 'string' ? input : input instanceof URL ? input.href : input.url; | |
| // Mock server props endpoint | |
| if (url.includes('/server')) { | |
| return new Response( | |
| JSON.stringify({ | |
| git_branch: 'test', | |
| git_commit: 'test', | |
| mode: 'router', | |
| version: 'test' | |
| }), | |
| { headers: { 'Content-Type': 'application/json' }, status: 200 } | |
| ); | |
| } | |
| // Mock models list endpoint | |
| if (/\/v1\/models|\/models\b/.test(url)) { | |
| return new Response( | |
| JSON.stringify({ | |
| data: [ | |
| { | |
| created: 0, | |
| id: 'test-model.gguf', | |
| in_cache: false, | |
| meta: {}, | |
| object: 'model', | |
| owned_by: 'llamacpp', | |
| path: 'models/test-model.gguf', | |
| status: { value: 'unloaded' } | |
| } | |
| ], | |
| models: [ | |
| { | |
| details: {}, | |
| model: 'test-model.gguf', | |
| name: 'Test Model' | |
| } | |
| ], | |
| object: 'list' | |
| }), | |
| { headers: { 'Content-Type': 'application/json' }, status: 200 } | |
| ); | |
| } | |
| // Mock /props endpoint (used for modalities) | |
| if (url.includes('/props')) { | |
| return new Response( | |
| JSON.stringify({ | |
| default_generation_settings: { n_ctx: 2048 } | |
| }), | |
| { headers: { 'Content-Type': 'application/json' }, status: 200 } | |
| ); | |
| } | |
| // Mock /tools endpoint (used for built-in tools list) | |
| if (url.includes('/tools')) { | |
| return new Response(JSON.stringify([]), { | |
| headers: { 'Content-Type': 'application/json' }, | |
| status: 200 | |
| }); | |
| } | |
| // Default: use real fetch | |
| return originalFetch(input, init); | |
| } | |
| ); | |
| }); | |