Instructions to use QuantFactory/Ahma-7B-GGUF 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 QuantFactory/Ahma-7B-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/Ahma-7B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/Ahma-7B-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/Ahma-7B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/Ahma-7B-GGUF: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 QuantFactory/Ahma-7B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf QuantFactory/Ahma-7B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/QuantFactory/Ahma-7B-GGUF:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use QuantFactory/Ahma-7B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "QuantFactory/Ahma-7B-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QuantFactory/Ahma-7B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/QuantFactory/Ahma-7B-GGUF:Q4_K_M
- Ollama
How to use QuantFactory/Ahma-7B-GGUF with Ollama:
ollama run hf.co/QuantFactory/Ahma-7B-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use QuantFactory/Ahma-7B-GGUF with Docker Model Runner:
docker model run hf.co/QuantFactory/Ahma-7B-GGUF:Q4_K_M
- Lemonade
How to use QuantFactory/Ahma-7B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull QuantFactory/Ahma-7B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Ahma-7B-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download Ahma-7B.Q3_K_M.gguf from QuantFactory/Ahma-7B-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 1.61 MB
-
https://huggingface.co/QuantFactory/Ahma-7B-GGUF/resolve/0110aa1b48bdc659eb348d6c94dc27d3c5e3063b/Ahma-7B.Q3_K_M.gguf
- Command line
-
hf download hf://QuantFactory/Ahma-7B-GGUF@0110aa1b48bdc659eb348d6c94dc27d3c5e3063b/Ahma-7B.Q3_K_M.gguf
-
curl -L -o Ahma-7B.Q3_K_M.gguf https://huggingface.co/QuantFactory/Ahma-7B-GGUF/resolve/0110aa1b48bdc659eb348d6c94dc27d3c5e3063b/Ahma-7B.Q3_K_M.gguf
1.61 MB
- Xet hash:
- 928213821ca7f2782f72889533475c00bc4dcd833562611cc85d568bc8bdffc3
- Size of remote file:
- 1.61 MB
- SHA256:
- ed717d48d8fa4650b6d23be1863a0e8d38a430753b2c2adee8b3b6eeb7a1a282
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