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 / audex_causal_speech_decoder /config.json

Arsh9210

Added audex_causal_speech_decoder/config.json

258c72d verified 10 days ago

Raw

History Blame

605 Bytes

	{
	"model_type": "audex_causal_speech_decoder",
	"architectures": [
	"AudexCausalSpeechDecoderModel"
	],
	"auto_map": {
	"AutoConfig": "configuration_audex_causal_speech_decoder.AudexCausalSpeechDecoderConfig",
	"AutoModel": "modeling_audex_causal_speech_decoder.AudexCausalSpeechDecoderModel"
	},
	"hidden_dim": 2048,
	"depth": 12,
	"heads": 32,
	"pos_meb_dim": 64,
	"hop_length": 320,
	"vq_dim": 2048,
	"lookahead_steps": 4,
	"sample_rate": 16000,
	"codebook_levels": [4, 4, 4, 4, 4, 4, 4, 4],
	"codebook_size": 65536,
	"token_embed_dim": 8,
	"embed_tokens_from_codes": true
	}