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model-index.json
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{
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"name": "MaskGCT",
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"_name_or_path": "amphion/MaskGCT",
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"modelId": "amphion/MaskGCT",
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"architectures": [
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"MaskGCTModel"
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],
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"model_type": "maskgct",
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"task_specific_params": {
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"text-to-speech": {
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"supported_tasks": [
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"zero-shot-tts",
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"non-autoregressive-tts"
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]
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}
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},
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"tags": [
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"text-to-speech",
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"safetensors"
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],
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"pipeline_tag": "text-to-speech",
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"language": [
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"en",
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"zh"
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],
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"license": "cc-by-nc-4.0",
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"datasets": [
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"Emilia-100k"
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],
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"model_structure": {
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"semantic_codec": {
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"type": "w2v-bert-2.0",
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"description": "Converting speech to semantic tokens"
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},
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"acoustic_codec": {
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"type": "codec",
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"description": "Converting speech to acoustic tokens and reconstructing waveform"
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},
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"maskgct_t2s": {
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"type": "transformer",
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"description": "Predicting semantic tokens with text and prompt semantic tokens"
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},
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"maskgct_s2a": {
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"variants": {
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"1layer": {
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"type": "transformer",
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"description": "Single layer model for acoustic token prediction"
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},
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"full": {
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"type": "transformer",
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"description": "Full model for acoustic token prediction"
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}
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},
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"description": "Predicts acoustic tokens conditioned on semantic tokens"
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}
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},
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"training_data": {
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"total_hours": 100000,
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"language_split": {
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"english": 50000,
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"chinese": 50000
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}
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},
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"paper": {
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"title": "MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer",
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"arxiv_id": "2409.00750"
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}
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}
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