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inclusionAI releases Ming-3.0-audio-flash, a 126B MoE audio-language model under MIT

AI summary

inclusionAI has published Ming-3.0-audio-flash on Hugging Face, a native audio-language model that takes audio together with text instructions and supports speech recognition, spoken question answering, audio understanding and audio reasoning, with optional synthesized-speech output. According to the model card, it is a Mixture-of-Experts model with 126B total parameters and 6.5B activated per inference step, with Chinese and English as primary languages and claimed support for accents, dialects and noisy multi-speaker recordings, released under the MIT license. The card documents Transformers, SGLang and vLLM-Omni deployment paths; the poster notes the four-GPU SGLang and eight 80GB H800 vLLM-Omni setups are reference configurations, not minimum requirements.

In-depth insight

The model card lists an MIT license and several documented deployment paths, and the poster argues that messy, overlapping-speaker recordings are the useful test of its value for a locally run voice assistant.

Ming-3.0-audio-flash is a native audio-language model from inclusionAI. It accepts audio together with text instructions and supports speech recognition, spoken question answering, audio understanding, audio reasoning, and optional synthesized-speech responses. Ming-3.0-audio-flash Hear clearly. Understand deeply. Act intelligently. Ming-3.0-audio-flash is a native audio-language model from inclusionAI. It accepts audio together with text instructions and supports speech recognition, spoken question answering, audio understanding, audio reasoning, and optional synthesized-speech responses. Model Summary Highlights submitted by /u/jacek2023 [link] [comments]

#inclusionAI#Ming-3.0-audio-flash#Hugging Face#ModelScope#SGLang#vLLM-Omni

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