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AI 모델 535

• CrisperWhisper2.0_small↗

  nyralabs

• faster-whisper-small↗

  Systran

  Note that the model weights are saved in FP16. This type can be changed when the model is loaded using the `compute_type` option in CTranslate2.

• ultravox-v0_3↗

  fixie-ai

  Ultravox is a multimodal Speech LLM built around a pretrained Llama3.1-8B-Instruct and Whisper-small backbone.\ See https://ultravox.ai for the GitHub repo and more information. Ultravox is a multimodal model that can consume both speech and text as input (e.g., a text system prompt and voice user message). The input to the model is given as a text prompt with a special ` ` pseudo-token, and the model processor will replace this magic token with embeddings derived from the input audio. Using the merged embeddings as input, the model will then generate output text as usual. In a future revision of Ultravox, we plan to expand the token vocabulary to support generation of semantic and acoustic audio tokens, which can then be fed to a vocoder to produce voice output. No preference tuning has been applied to this revision of the model.

• Whisper-Large-v3-Turbo-CoreML↗

  aufklarer

• moonshine-tiny↗

  moonshine-ai

  This is the model card for running the automatic speech recognition (ASR) models (Moonshine models) trained and released by Useful Sensors. Following Model Cards for Model Reporting (Mitchell et al.), we're providing some information about the automatic speech recognition model. More information on how these models were trained and evaluated can be found in the paper. Note, a lot of the text has been copied verbatim from the model card for the Whisper model developed by OpenAI, because both models serve identical purposes, and carry identical risks. Moonshine is supported in Hugging Face 🤗 Transformers. To run the model, first install the Transformers library. For this example, we'll also install 🤗 Datasets to load toy audio dataset from the Hugging Face Hub, and 🤗 Accelerate to reduce the model loading time:

• whisper-base.en_timestamped↗

  onnx-community

  https://huggingface.co/openai/whisper-base.en 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`).

• whisper-small-asr-fp16↗

  mlx-community

• whisper-telephony-amd↗

  AbijahKaj

• kb-whisper-base↗

  KBLab

• anime-whisper-ct2-int8↗

  quantumcookie