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AI モデル 535

• whisper-small↗

  onnx-community

  https://huggingface.co/openai/whisper-small with ONNX weights to be compatible with Transformers.js. Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).

• MiniCPM-o-4_5-gguf↗

  openbmb

  A Gemini 2.5 Flash Level MLLM for Vision, Speech, and Full-Duplex Mulitmodal Live Streaming on Your Phone > [!NOTE] > [2026.02.06] 🥳 🥳 🥳 We open-sourced a realtime web demo deployable on your own devices like Mac or GPU. Try it now! **MiniCPM-o 4.5** is the latest and most capable model in the MiniCPM-o series. The model is built in an end-to-end fashion based on SigLip2, Whisper-medium, CosyVoice2, and Qwen3-8B with a total of 9B parameters. It exhibits a significant performance improvement, and introduces new features for full-duplex multimodal live streaming. Notable features of MiniCPM-o 4.5 include:

• Whisper-V3-Turbo-NPU2↗

  FastFlowLM

• whisper-small.en-int8-ov↗

  OpenVINO

• distil-large-v3↗

  distil-whisper

  Distil-Whisper was proposed in the paper Robust Knowledge Distillation via Large-Scale Pseudo Labelling. This is the third and final installment of the Distil-Whisper English series. It the knowledge distilled version of OpenAI's Whisper large-v3, the latest and most performant Whisper model to date. Compared to previous Distil-Whisper models, the distillation procedure for distil-large-v3 has been adapted to give **superior long-form transcription accuracy** with OpenAI's **sequential long-form algorithm**.

• nb-whisper-coreml↗

  Barrymanalow

  **This is a format conversion, not a new model.** No retraining, no fine-tuning, no distillation. Weights and behaviour are NbAiLab's; the changes are the PyTorch → CoreML conversion and the folder layout WhisperKit expects. All credit for the model belongs to NbAiLab. Float16 activations. The layout mirrors `argmaxinc/whisperkit-coreml`, which is what `WhisperKitConfig(model:modelRepo:)` expects to find. With papegøye, a bilingual Norwegian/English macOS dictation daemon — it downloads this repo automatically:

• whisper-medium↗

  litert-community

• kotoba-whisper-v2.2-coreml↗

  yslinear

• whisper-large-v3-turbo-sq-v2↗

  Flutra

• whisper-large-v3-vaani-hindi↗

  ARTPARK-IISc

  This is a fine-tuned version of OpenAI's Whisper-Large-V3, trained on approximately 718 hours of transcribed Hindi speech from multiple datasets. The models has finetuned using folllowing dataset Vaani ,Gramvaani IndicVoices, Fleurs,IndicTTS and Commonvoice The performance of the model was evaluated using multiple datasets, and the evaluation results are provided below.