Instructions to use tpsjr7/acestep-captioner-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 tpsjr7/acestep-captioner-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 tpsjr7/acestep-captioner-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf tpsjr7/acestep-captioner-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 tpsjr7/acestep-captioner-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf tpsjr7/acestep-captioner-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 tpsjr7/acestep-captioner-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf tpsjr7/acestep-captioner-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 tpsjr7/acestep-captioner-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf tpsjr7/acestep-captioner-GGUF:Q4_K_M
Use Docker
docker model run hf.co/tpsjr7/acestep-captioner-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use tpsjr7/acestep-captioner-GGUF with Ollama:
ollama run hf.co/tpsjr7/acestep-captioner-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use tpsjr7/acestep-captioner-GGUF with Docker Model Runner:
docker model run hf.co/tpsjr7/acestep-captioner-GGUF:Q4_K_M
- Lemonade
How to use tpsjr7/acestep-captioner-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tpsjr7/acestep-captioner-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.acestep-captioner-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
ACE-Step Captioner GGUF
This repository contains a llama.cpp-compatible GGUF conversion of ACE-Step/acestep-captioner.
The initial upload is intended to include:
acestep-captioner-Q4_K_M.ggufacestep-captioner-Q6_K.ggufacestep-captioner-Q8_0.ggufacestep-captioner-mmproj-bf16.gguf
Files
acestep-captioner-Q4_K_M.gguf: Quantized text model for inference withllama.cppacestep-captioner-Q6_K.gguf: Higher-quality 6-bit quantized text modelacestep-captioner-Q8_0.gguf: Higher-quality 8-bit quantized text modelacestep-captioner-mmproj-bf16.gguf: Multimodal projector required for audio input
llama.cpp
This model requires a recent llama.cpp build with Qwen2.5-Omni audio support.
Tested with this fork / branch which fixed audio inference bugs: https://github.com/tpsjr7/llama.cpp/tree/ted/fix-qwen-audio-cleanup-merge
Example:
llama-cli -m ./acestep-captioner-Q4_K_M.gguf \
--mmproj ./acestep-captioner-mmproj-bf16.gguf \
--audio ./song.mp3 \
-p "*Task* Describe this audio in detail" \
-n 512 --temp 0 --single-turn --simple-io -ngl 999 --ctx-size 8192
Swap in acestep-captioner-Q6_K.gguf or acestep-captioner-Q8_0.gguf if you want a less aggressive quantization.
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Base model
ACE-Step/acestep-captioner