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/enums/server.enums.ts from VladHong/llama-cpp-K2-FAST2: direct link, hf CLI and curl.
- Browser
- Download file 1.02 kB
-
https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/src/lib/enums/server.enums.ts
- Command line
-
hf download hf://VladHong/llama-cpp-K2-FAST2/tools/ui/src/lib/enums/server.enums.ts
-
curl -L -o server.enums.ts https://huggingface.co/VladHong/llama-cpp-K2-FAST2/resolve/main/tools/ui/src/lib/enums/server.enums.ts
1.02 kB
| /** | |
| * Server role enum - used for single/multi-model mode | |
| */ | |
| export enum ServerRole { | |
| /** Single model mode - server running with a specific model loaded */ | |
| MODEL = 'model', | |
| /** Router mode - server managing multiple model instances */ | |
| ROUTER = 'router' | |
| } | |
| /** | |
| * Model status enum - matches tools/server/server-models.h from C++ server | |
| * Used as the `value` field in the status object from /models endpoint | |
| */ | |
| export enum ServerModelStatus { | |
| FAILED = 'failed', | |
| LOADED = 'loaded', | |
| LOADING = 'loading', | |
| SLEEPING = 'sleeping', | |
| UNLOADED = 'unloaded' | |
| } | |
| /** | |
| * /models/sse event type enum - discriminates the records broadcast on the | |
| * model status feed in ROUTER mode. Matches the event names emitted by | |
| * tools/server/server-models.cpp from the C++ server. | |
| */ | |
| export enum ServerModelsSseEventType { | |
| DOWNLOAD_PROGRESS = 'download_progress', | |
| MODEL_REMOVE = 'model_remove', | |
| MODEL_STATUS = 'model_status', | |
| MODELS_RELOAD = 'models_reload', | |
| STATUS_CHANGE = 'status_change', | |
| STATUS_UPDATE = 'status_update' | |
| } | |