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TText generation▧Image generation▷Video generation⌘Code generation◖Speech synthesis♫Music generation⬡3D modeling▤Document analysis
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This model is a custom 5-block convolutional network, trained from scratch (no ImageNet pretraining) on single-channel 128x128 fetal ultrasound images, to classify fetal ultrasound standard planes. No explicit description provided in dataset metadata. Changes Made Removed the pooling on the final layer. Lowered lr = 1e-5 effective batch size 32 ---

Image classification
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BertMeshTerms

marcmendez-aily

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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Mythos-nano

marcosvpj

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Text generation
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This is the SPEAR Large dual-domain (speech + general audio) model. The model adopts a Zipformer backbone with 327M parameters consisting of 112 Zipformer stacks. It generates 1024-dimensional representations at approximately 50~Hz. This model was pre-trained on 97k hours of mixture data of English speech and general audio, among which 84k hours are speech data, and the remaining 13k hours are general audio data. It achieves high performance on SUPERB benchmark (for speech representation evaluation) and on HEAR benchmark (for audio representation evaluation). **Note**: The model is pretrained on 16kHz sampled speech/audio data. When using the model make sure that your input is also sampled at 16kHz.

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