Instructions to use audarai/Audar-ASR-V1-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use audarai/Audar-ASR-V1-Turbo with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("automatic-speech-recognition", model="audarai/Audar-ASR-V1-Turbo", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("audarai/Audar-ASR-V1-Turbo", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("audarai/Audar-ASR-V1-Turbo", trust_remote_code=True, device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

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

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

Atomic Chat

Audar-ASR-V1-Turbo / generation_config.json

Dragonhead

Release full-precision bf16 safetensors at repo root (loads via from_pretrained + trust_remote_code, transformers==4.57.6); remove transformers/ subfolder (remote-code needs root)

c2ebfc4 verified 13 days ago

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131 Bytes

	{
	"_from_model_config": true,
	"eos_token_id": [
	151645
	],
	"pad_token_id": 151643,
	"transformers_version": "4.57.6"
	}