Instructions to use Mattral/Nemotron-Labs-Audex-30B-A3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Mattral/Nemotron-Labs-Audex-30B-A3B with Transformers:

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

pipe = pipeline("text-generation", model="Mattral/Nemotron-Labs-Audex-30B-A3B")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Mattral/Nemotron-Labs-Audex-30B-A3B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Mattral/Nemotron-Labs-Audex-30B-A3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Mattral/Nemotron-Labs-Audex-30B-A3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Mattral/Nemotron-Labs-Audex-30B-A3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Mattral/Nemotron-Labs-Audex-30B-A3B

SGLang

How to use Mattral/Nemotron-Labs-Audex-30B-A3B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Mattral/Nemotron-Labs-Audex-30B-A3B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Mattral/Nemotron-Labs-Audex-30B-A3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Mattral/Nemotron-Labs-Audex-30B-A3B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Mattral/Nemotron-Labs-Audex-30B-A3B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Mattral/Nemotron-Labs-Audex-30B-A3B with Docker Model Runner:
```
docker model run hf.co/Mattral/Nemotron-Labs-Audex-30B-A3B
```

Nemotron-Labs-Audex-30B-A3B

File size: 1,076 Bytes

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{
  "model_type": "autoencoder",
  "sample_size": 96000,
  "sample_rate": 48000,
  "audio_channels": 1,
  "model": {
    "encoder": {
      "type": "spec_convnext",
      "config": {
        "in_channels": 1,
        "channels": 512,
        "c_mults": [1, 2, 4],
        "strides": [4, 5, 6],
        "latent_dim": 1024,
        "identity_init": false,
        "n_fft": 64,
        "hop_length": 16,
        "use_snake": true,
        "causal": true,
        "padding_mode": "reflect"
      }
    },
    "decoder": {
      "type": "oobleck",
      "config": {
        "out_channels": 1,
        "channels": 320,
        "c_mults": [1, 2, 4, 8, 16],
        "strides": [2, 4, 5, 6, 8],
        "latent_dim": 512,
        "use_snake": true,
        "final_tanh": false,
        "causal": true,
        "padding_mode": "reflect"
      }
    },
    "bottleneck": {
      "type": "vae_distillation",
      "config": {
        "latent_dim": 512,
        "distillation_proj_dim": 1024
      }
    },
    "latent_dim": 512,
    "downsampling_ratio": 1920,
    "io_channels": 1
  }
}