Instructions to use foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF", filename="Qwen3-ASR-1.7B-Q4_K_M.gguf", )
llm.create_chat_completion( messages = "\"sample1.flac\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf foryoung365/Qwen3-ASR-1.7B-Q4_K_M-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 foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf foryoung365/Qwen3-ASR-1.7B-Q4_K_M-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 foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF:Q4_K_M
Use Docker
docker model run hf.co/foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF with Ollama:
ollama run hf.co/foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF:Q4_K_M
- Unsloth Studio
How to use foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF with Docker Model Runner:
docker model run hf.co/foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF:Q4_K_M
- Lemonade
How to use foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Qwen3-ASR-1.7B-Q4_K_M-GGUF-Q4_K_M
List all available models
lemonade list
Qwen3-ASR-1.7B-Q4_K_M-GGUF
GGUF export of Qwen/Qwen3-ASR-1.7B for llama.cpp.
Files included:
Qwen3-ASR-1.7B-Q4_K_M.ggufmmproj-Qwen3-ASR-1.7B-Q4_K_M.gguf
Both files are required for audio transcription with llama.cpp multimodal support.
Tested command
llama-mtmd-cli.exe ^
-m Qwen3-ASR-1.7B-Q4_K_M.gguf ^
--mmproj mmproj-Qwen3-ASR-1.7B-Q4_K_M.gguf ^
--audio sample.wav ^
-p "Transcribe the audio." ^
-t 8 -n 256 --temp 0
Notes
- Main model was converted from the original Hugging Face checkpoint to GGUF, then quantized to
Q4_K_M. mmprojwas exported from the original checkpoint asF16, then quantized toQ4_K_M.- This pair was locally tested with
llama-mtmd-clion Chinese audio.
- Downloads last month
- 421
Hardware compatibility
Log In to add your hardware
4-bit
Model tree for foryoung365/Qwen3-ASR-1.7B-Q4_K_M-GGUF
Base model
Qwen/Qwen3-ASR-1.7B