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
```

Arsh9210 commited on 10 days ago

Commit

47a7df4

verified ·

1 Parent(s): 208d113

Added enhancement_VAE/config.json

Browse files

Files changed (1) hide show

enhancement_VAE/config.json +48 -0

enhancement_VAE/config.json ADDED Viewed

	@@ -0,0 +1,48 @@

+{
+  "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
+  }
+}