전체 검색

AI 모델 84759

• personaplex-7b-v1↗

  NVIDIA

• AgentCPM-Explore↗

  openbmb

• Qwen3-1.7B-Wordle-SFT↗

  openenv

• InternVL3-78B-Pretrained↗

  OpenGVLab

• MOSS-Audio-4B-Instruct↗

  OpenMOSS-Team

  MOSS-Audio is an open-source **audio understanding model** from MOSI.AI, the OpenMOSS team, and Shanghai Innovation Institute. It performs unified modeling over complex real-world audio, supporting **speech understanding, environmental sound understanding, music understanding, audio captioning, time-aware QA, and complex reasoning**. In this release, we provide **four models**: **MOSS-Audio-4B-Instruct**, **MOSS-Audio-4B-Thinking**, **MOSS-Audio-8B-Instruct**, and **MOSS-Audio-8B-Thinking**. The Instruct variants are optimized for direct instruction following, while the Thinking variants provide stronger chain-of-thought reasoning capabilities. Understanding audio requires more than simply transcribing words — it demands the ability to perceive acoustic cues, recognize speakers and emotions, interpret environmental sounds, reason over temporal context, and handle complex multi-step inference. **MOSS-Audio** is built to unify these capabilities within a single model. MOSS-Audio follows a modular design comprising three components: an audio encoder, a modality adapter, and a large language model. Raw audio is first encoded by **MOSS-Audio-Encoder** into continuous temporal representations at **12.5 Hz**, which are then projected into the language model's embedding space through the adapter and finally consumed by the LLM for auto-regressive text generation.

• UCSCPhytoViT83↗

  patcdaniel

• Ternary-Bonsai-27B-unpacked↗

  prism-ml

• L3-Luna-8B-GGUF↗

  QuantFactory

• TIPO-500M-GGUF↗

  QuantFactory

• anime-whisper-ct2-int8↗

  quantumcookie