Token Classification
GGUF
Safetensors
Chinese
input-method
zhuyin
bopomofo
traditional-chinese
ternary
bitnet
Instructions to use Luigi/sloth-ime-models 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 Luigi/sloth-ime-models 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 Luigi/sloth-ime-models # Run inference directly in the terminal: llama cli -hf Luigi/sloth-ime-models
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Luigi/sloth-ime-models # Run inference directly in the terminal: llama cli -hf Luigi/sloth-ime-models
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Luigi/sloth-ime-models # Run inference directly in the terminal: ./llama-cli -hf Luigi/sloth-ime-models
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Luigi/sloth-ime-models # Run inference directly in the terminal: ./build/bin/llama-cli -hf Luigi/sloth-ime-models
Use Docker
docker model run hf.co/Luigi/sloth-ime-models
- LM Studio
- Jan
- Ollama
How to use Luigi/sloth-ime-models with Ollama:
ollama run hf.co/Luigi/sloth-ime-models
- Unsloth Studio
How to use Luigi/sloth-ime-models with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Luigi/sloth-ime-models to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Luigi/sloth-ime-models to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Luigi/sloth-ime-models to start chatting
- Docker Model Runner
How to use Luigi/sloth-ime-models with Docker Model Runner:
docker model run hf.co/Luigi/sloth-ime-models
- Lemonade
How to use Luigi/sloth-ime-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Luigi/sloth-ime-models
Run and chat with the model
lemonade run user.sloth-ime-models-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
| { | |
| "n_syl": 1539, | |
| "n_char": 8342, | |
| "dim": 352, | |
| "depth": 16, | |
| "heads": 8, | |
| "kv": 2, | |
| "ffn": 960, | |
| "embed_norm": true, | |
| "weight_bits": "ternary", | |
| "weight_quant": "median", | |
| "fp_boundary": 1, | |
| "pre_norm": true, | |
| "act_bits": 8, | |
| "char_hints": false, | |
| "tie_hints": false | |
| } |