Duplicate from tsukumijima/deberta-v3-large-onnx

Co-authored-by: tsukumi <tsukumijima@users.noreply.huggingface.co>

.gitattributes

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README.md

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+---
+license: mit
+language:
+- ja
+base_model:
+- microsoft/deberta-v3-large
+---
+
+Style-Bert-VITS2 の ONNX 推論コード向けに ONNX 形式へ変換した [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) です。  
+変換コードは https://github.com/tsukumijima/Style-Bert-VITS2/blob/master/convert_bert_onnx.py にあります。
+
+> [!NOTE]
+> モデルの軽量化のため、BERT の隠れ層 (hidden states) のうち、Style-Bert-VITS2 で用いる最後から3番目の隠れ層のみを言語特徴量として抽出する ONNX モデルとして変換しています。  
+> そのため、事実上 Style-Bert-VITS2 の ONNX 推論以外での使い道はないと思います。

config.json

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+{
+		"model_type": "deberta-v2",
+		"attention_probs_dropout_prob": 0.1,
+		"hidden_act": "gelu",
+		"hidden_dropout_prob": 0.1,
+		"hidden_size": 1024,
+		"initializer_range": 0.02,
+		"intermediate_size": 4096,
+		"max_position_embeddings": 512,
+		"relative_attention": true,
+		"position_buckets": 256,
+		"norm_rel_ebd": "layer_norm",
+		"share_att_key": true,
+		"pos_att_type": "p2c|c2p",
+		"layer_norm_eps": 1e-7,
+		"max_relative_positions": -1,
+		"position_biased_input": false,
+		"num_attention_heads": 16,
+		"num_hidden_layers": 24,
+		"type_vocab_size": 0,
+		"vocab_size": 128100
+}

generator_config.json

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+{
+	"model_type": "deberta-v2",
+	"attention_probs_dropout_prob": 0.1,
+	"hidden_act": "gelu",
+	"hidden_dropout_prob": 0.1,
+	"hidden_size": 1024,
+	"initializer_range": 0.02,
+	"intermediate_size": 4096,
+	"max_position_embeddings": 512,
+	"relative_attention": true,
+	"position_buckets": 256,
+	"norm_rel_ebd": "layer_norm",
+	"share_att_key": true,
+	"pos_att_type": "p2c|c2p",
+	"layer_norm_eps": 1e-7,
+	"max_relative_positions": -1,
+	"position_biased_input": false,
+	"num_attention_heads": 16,
+	"num_hidden_layers": 12,
+	"type_vocab_size": 0,
+	"vocab_size": 128100
+}

model.onnx

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model_fp16.onnx

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spm.model

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tokenizer_config.json

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+{
+  "do_lower_case": false,
+  "vocab_type": "spm"
+}