Instructions to use HsuSin/TC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HsuSin/TC with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HsuSin/TC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use HsuSin/TC 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 HsuSin/TC:Q4_K_M # Run inference directly in the terminal: llama cli -hf HsuSin/TC:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf HsuSin/TC:Q4_K_M # Run inference directly in the terminal: llama cli -hf HsuSin/TC:Q4_K_M
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 HsuSin/TC:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf HsuSin/TC:Q4_K_M
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 HsuSin/TC:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf HsuSin/TC:Q4_K_M
Use Docker
docker model run hf.co/HsuSin/TC:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use HsuSin/TC with Ollama:
ollama run hf.co/HsuSin/TC:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use HsuSin/TC with Docker Model Runner:
docker model run hf.co/HsuSin/TC:Q4_K_M
- Lemonade
How to use HsuSin/TC with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HsuSin/TC:Q4_K_M
Run and chat with the model
lemonade run user.TC-Q4_K_M
List all available models
lemonade list
- Atomic Chat
- Xet hash:
- 1b4a49a2af3f6daf2c2a3f3672379ad87020757c937c99bd1487637c76139f14
- Size of remote file:
- 4.37 GB
- SHA256:
- 645a9a8c403e0c8340db4cf2f4a8398e35d49be1af76b9b8cdaa6c9d1a3469ca
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