Text Generation
Transformers
Safetensors
English
nemotron_labs_audex
nvidia
nemotron-labs-audex
reasoning
general-purpose
SFT
audio-language-modeling
audio-understanding
text-to-speech
text-to-audio
speech-recognition
speech-translation
Instructions to use Arsh9210/Nemotron-Labs-Audex-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
Added checkpoint_folder_audiogen/special_tokens_map.json
Browse files
checkpoint_folder_audiogen/special_tokens_map.json
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{
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"additional_special_tokens": [
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"<audiogen>",
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"<audiogen_start>",
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"<audiogen_end>",
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"<speechgen_start>",
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"<speechgen_end>"
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],
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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