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README.md
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- **Language(s) (NLP):** English, Chinese, Vietnamese, Indonesian, Thai, Filipino, Tamil, Malay, Khmer, Lao, Burmese, Javanese, Sundanese, etc.
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- **License:** to be advised
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We support model inference using the [Huggingface](#inference) and [vLLM](#vllm-inference) frameworks. For more technical details, please refer to our [report]().
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## Model Description
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The current MERaLiON-AudioLLM has not been specifically aligned for safety and may generate content that is inappropriate, offensive, or harmful. Developers and users are responsible for performing their own safety fine-tuning and implementing necessary security measures. The authors shall not be held liable for any claims, damages, or other liabilities arising from the use of the released models, weights, or code.
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This research is supported by the National Research Foundation, Singapore, and Infocomm Media Development Authority, Singapore under its National Large Language Models Funding Initiative. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore and Infocomm Media Development Authority, Singapore.
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## Technical Specifications
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### Training Data
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- **Language(s) (NLP):** English, Chinese, Vietnamese, Indonesian, Thai, Filipino, Tamil, Malay, Khmer, Lao, Burmese, Javanese, Sundanese, etc.
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- **License:** to be advised
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We support model inference using the [Huggingface](#inference) and [vLLM](#vllm-inference) frameworks. For more technical details, please refer to our [technical report](https://arxiv.org/abs/2412.09818).
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## Acknowledgement
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This research is supported by the National Research Foundation, Singapore and Infocomm Media Development Authority, Singapore under its National Large Language Models Funding Initiative.
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## Model Description
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The current MERaLiON-AudioLLM has not been specifically aligned for safety and may generate content that is inappropriate, offensive, or harmful. Developers and users are responsible for performing their own safety fine-tuning and implementing necessary security measures. The authors shall not be held liable for any claims, damages, or other liabilities arising from the use of the released models, weights, or code.
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## Technical Specifications
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### Training Data
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