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README.md
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license: other
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language:
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- en
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tags:
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- audio
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- reasoning
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- audio understanding
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- ASR
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---
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# Model Overview
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**This model is for non-commercial research purposes only.**
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<
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<center><img src="static/af3_main_diagram-1.png" width="800"></center>
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**This model was developed based on [NVILA](https://github.com/NVlabs/VILA/tree/main/scripts/NVILA-Lite) and [Qwen-2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) <br>
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## Input:
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Input Type: Audio, Text <br>
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Input Format: WAV/MP3/FLAC, UTF-8 text <br>
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Input Parameters: Audio is Two-Dimensional (2D) and Text is One-Dimensional (1D)<br>
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Other Properties Related to Input: <br>
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-Max Audio Length: 10 Minutes <br>
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-Max Text Length: 16000 tokens<br>
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## Output:
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Output Type: Text (and optional speech) <br>
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Text Format: UTF-8 string <br>
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Output Parameters: One-Dimensional (1D)<br>
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Other Properties Related to Output: <br>
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-Max Text Length: 1024 tokens <br>
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-Speech Format: streaming TTS (text-to-speech) waveform<br>
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Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems (A100/H100). By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions. <br>
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---
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## Acknowledgements
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Built with Qwen, NVILA and the open audio-ML community.
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license: other
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language:
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- en
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arxiv: 2503.03983
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tags:
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- audio
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- reasoning
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- audio understanding
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- ASR
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datasets:
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- nvidia/AudioSkills
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- nvidia/AF-Chat
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- nvidia/AF-Think
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- nvidia/LongAudio
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---
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# Model Overview
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**This model is for non-commercial research purposes only.**
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## Model Architecture:
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Audio Flamingo 3 uses AF-Whisper unified audio encoder, MLP-based audio adaptor, Decoder-only LLM backbone (Qwen2.5-7B), and Streaming TTS module (AF3-Chat). Audio Flamingo 3 can take up to 10 minutes of audio inputs.
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<center><img src="static/af3_radial-1.png" width="400"></center>
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## Results:
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<center><img src="static/af3_main_diagram-1.png" width="800"></center>
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**This model was developed based on [NVILA](https://github.com/NVlabs/VILA/tree/main/scripts/NVILA-Lite) and [Qwen-2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) <br>
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## Input:
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- Input Type: Audio, Text <br>
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- Input Format: WAV/MP3/FLAC, UTF-8 text <br>
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- Input Parameters: Audio is Two-Dimensional (2D) and Text is One-Dimensional (1D)<br>
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- Other Properties Related to Input: <br>
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- Max Audio Length: 10 Minutes <br>
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- Max Text Length: 16000 tokens<br>
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## Output:
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- Output Type: Text (and optional speech) <br>
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- Text Format: UTF-8 string <br>
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- Output Parameters: One-Dimensional (1D)<br>
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- Other Properties Related to Output: <br>
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- Max Text Length: 1024 tokens <br>
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- Speech Format: streaming TTS (text-to-speech) waveform<br>
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Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems (A100/H100). By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions. <br>
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---
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## Acknowledgements
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Built with Qwen, NVILA and the open audio-ML community.
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