Instructions to use Arsh9210/Nemotron-Labs-Audex-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Arsh9210/Nemotron-Labs-Audex-2B with Transformers:

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

pipe = pipeline("text-generation", model="Arsh9210/Nemotron-Labs-Audex-2B")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Arsh9210/Nemotron-Labs-Audex-2B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Arsh9210/Nemotron-Labs-Audex-2B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Arsh9210/Nemotron-Labs-Audex-2B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Arsh9210/Nemotron-Labs-Audex-2B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Arsh9210/Nemotron-Labs-Audex-2B

SGLang

How to use Arsh9210/Nemotron-Labs-Audex-2B 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 "Arsh9210/Nemotron-Labs-Audex-2B" \
    --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": "Arsh9210/Nemotron-Labs-Audex-2B",
		"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 "Arsh9210/Nemotron-Labs-Audex-2B" \
        --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": "Arsh9210/Nemotron-Labs-Audex-2B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Arsh9210/Nemotron-Labs-Audex-2B with Docker Model Runner:
```
docker model run hf.co/Arsh9210/Nemotron-Labs-Audex-2B
```

Nemotron-Labs-Audex-2B / enhancement_VAE /config.json

Arsh9210

Added enhancement_VAE/config.json

47a7df4 verified 10 days ago

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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
	}
	}