How to use mradermacher/Qwen2-7B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/Qwen2-7B-GGUF", device_map="auto")
How to use mradermacher/Qwen2-7B-GGUF with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf mradermacher/Qwen2-7B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Qwen2-7B-GGUF:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mradermacher/Qwen2-7B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mradermacher/Qwen2-7B-GGUF:Q4_K_M
# 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 mradermacher/Qwen2-7B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/Qwen2-7B-GGUF:Q4_K_M
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 mradermacher/Qwen2-7B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/Qwen2-7B-GGUF:Q4_K_M
docker model run hf.co/mradermacher/Qwen2-7B-GGUF:Q4_K_M
How to use mradermacher/Qwen2-7B-GGUF with Ollama:
ollama run hf.co/mradermacher/Qwen2-7B-GGUF:Q4_K_M
How to use mradermacher/Qwen2-7B-GGUF with Docker Model Runner:
How to use mradermacher/Qwen2-7B-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/Qwen2-7B-GGUF:Q4_K_M
lemonade run user.Qwen2-7B-GGUF-Q4_K_M
lemonade list
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