Instructions to use matteogeniaccio/GLM-4-32B-0414-GGUF-fixed 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 matteogeniaccio/GLM-4-32B-0414-GGUF-fixed 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 matteogeniaccio/GLM-4-32B-0414-GGUF-fixed:Q4_K_M # Run inference directly in the terminal: llama cli -hf matteogeniaccio/GLM-4-32B-0414-GGUF-fixed:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf matteogeniaccio/GLM-4-32B-0414-GGUF-fixed:Q4_K_M # Run inference directly in the terminal: llama cli -hf matteogeniaccio/GLM-4-32B-0414-GGUF-fixed:Q4_K_M
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 matteogeniaccio/GLM-4-32B-0414-GGUF-fixed:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf matteogeniaccio/GLM-4-32B-0414-GGUF-fixed:Q4_K_M
Use Docker
docker model run hf.co/matteogeniaccio/GLM-4-32B-0414-GGUF-fixed:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use matteogeniaccio/GLM-4-32B-0414-GGUF-fixed with Ollama:
ollama run hf.co/matteogeniaccio/GLM-4-32B-0414-GGUF-fixed:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use matteogeniaccio/GLM-4-32B-0414-GGUF-fixed with Docker Model Runner:
docker model run hf.co/matteogeniaccio/GLM-4-32B-0414-GGUF-fixed:Q4_K_M
- Lemonade
How to use matteogeniaccio/GLM-4-32B-0414-GGUF-fixed with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull matteogeniaccio/GLM-4-32B-0414-GGUF-fixed:Q4_K_M
Run and chat with the model
lemonade run user.GLM-4-32B-0414-GGUF-fixed-Q4_K_M
List all available models
lemonade list
- Atomic Chat
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Check out the documentation for more information.
This fixes a template bug in llama.cpp and ollama that is causing a performance degradation in all GLM models.
The problem is caused by a wrong template detection in both projects.
https://github.com/ollama/ollama/issues/10408 https://github.com/ggml-org/llama.cpp/pull/13099
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