EAT-base_epoch30_finetune_AS2M is the epoch 30 fine-tuned checkpoint of the EAT-base audio model. It uses self-supervised learning to generate high-quality audio embeddings. The model is compatible with the Hugging Face transformers library and is intended for researchers and developers working on audio understanding tasks.
EAT Base Epoch30 Finetune AS2M sits in PulseGate's Foundation models & chat category. It focuses on creating rich audio representations from raw audio data for downstream tasks such as classification and retrieval using self-supervised pretraining. It is built as an open-source project for developers. The project is open source (MIT). It runs on the web and API.
It is developed by worstchan, and it first shipped in 2023. The project is developed in the open on GitHub with 236 stars. Among its 3 catalogued features are Audio Embeddings, Self-Supervised Learning, and Feature Extraction.
Summary written by a language model from the project’s public pages.
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