Automatic Speech Recognition
Safetensors
GGUF
Arabic
English
asr
speech-recognition
arabic
arabic-asr
dialectal-arabic
emirati
gulf-arabic
streaming
realtime
llama-cpp
audar
conversational
Instructions to use audarai/Audar-ASR-V1-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use audarai/Audar-ASR-V1-Turbo with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="audarai/Audar-ASR-V1-Turbo", filename="Audar-ASR-V1-Turbo-Q4_K_M.gguf", )
llm.create_chat_completion( messages = "\"sample1.flac\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use audarai/Audar-ASR-V1-Turbo 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 audarai/Audar-ASR-V1-Turbo:Q4_K_M # Run inference directly in the terminal: llama cli -hf audarai/Audar-ASR-V1-Turbo:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf audarai/Audar-ASR-V1-Turbo:Q4_K_M # Run inference directly in the terminal: llama cli -hf audarai/Audar-ASR-V1-Turbo: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 audarai/Audar-ASR-V1-Turbo:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf audarai/Audar-ASR-V1-Turbo: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 audarai/Audar-ASR-V1-Turbo:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf audarai/Audar-ASR-V1-Turbo:Q4_K_M
Use Docker
docker model run hf.co/audarai/Audar-ASR-V1-Turbo:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use audarai/Audar-ASR-V1-Turbo with Ollama:
ollama run hf.co/audarai/Audar-ASR-V1-Turbo:Q4_K_M
- Unsloth Studio
How to use audarai/Audar-ASR-V1-Turbo 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 audarai/Audar-ASR-V1-Turbo 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 audarai/Audar-ASR-V1-Turbo to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for audarai/Audar-ASR-V1-Turbo to start chatting
- Atomic Chat new
- Docker Model Runner
How to use audarai/Audar-ASR-V1-Turbo with Docker Model Runner:
docker model run hf.co/audarai/Audar-ASR-V1-Turbo:Q4_K_M
- Lemonade
How to use audarai/Audar-ASR-V1-Turbo with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull audarai/Audar-ASR-V1-Turbo:Q4_K_M
Run and chat with the model
lemonade run user.Audar-ASR-V1-Turbo-Q4_K_M
List all available models
lemonade list
vllm compatible release?
#1
by ast980 - opened
Thanks for releasing this model. Is it possible to adapt it to run on vllm?
Yes, it is possible to run it on vllm. we have added some notes on the model card for vll deployments. Check this section: "vLLM inference (GPU serving)".
Thank you so much! Is it also possible to run Audar-TTS-V1-Turbo on vllm-omni?