Instructions to use QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF 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 QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF: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 QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF: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 QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF:Q4_K_M
Use Docker
docker model run hf.co/QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF with Ollama:
ollama run hf.co/QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF with Docker Model Runner:
docker model run hf.co/QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF:Q4_K_M
- Lemonade
How to use QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull QuantFactory/Yi-Coder-9B-Chat-Instruct-TIES-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Yi-Coder-9B-Chat-Instruct-TIES-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
- Xet hash:
- b8231995bc4dd530d8399b8c1915c7848593b16edd938b125b43919e099bdd35
- Size of remote file:
- 4.32 GB
- SHA256:
- 4d8cc0a72d6b7639383bda20290724813c278eaee760a6a829b35e353343063a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.