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 Desktop
- 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
add 12M ternary 256x12 sibling (9.65MB TQ2_0, 84%/84%, 9.3ms@4t on BOOX)
Browse files- .gitattributes +1 -0
- slothe-t-12m-256x12.gguf +3 -0
.gitattributes
CHANGED
|
@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
slothe-t-25m.gguf filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
slothe-t-25m.gguf filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
slothe-t-12m-256x12.gguf filter=lfs diff=lfs merge=lfs -text
|
slothe-t-12m-256x12.gguf
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e68cf9ee8b8d444bf0407addd20a79d5149d9ebbca0162971277e09918a7c151
|
| 3 |
+
size 10115712
|