rightyonghu
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Browse files- README.md +2 -6
- config.json +19 -18
- flax_model.msgpack +0 -3
- pytorch_model.bin +2 -2
- tf_model.h5 +0 -3
README.md
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## Released Model Info
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|Model Name|Language|Model Structure|
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|ernie-2.0-en| English |Layer:12, Hidden:768, Heads:12|
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This released pytorch model is converted from the officially released PaddlePaddle ERNIE model and
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a series of experiments have been conducted to check the accuracy of the conversion.
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## How to use
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```Python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("nghuyong/ernie-2.0-en")
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model = AutoModel.from_pretrained("nghuyong/ernie-2.0-en")
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```
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## Citation
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## Released Model Info
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This released pytorch model is converted from the officially released PaddlePaddle ERNIE model and
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a series of experiments have been conducted to check the accuracy of the conversion.
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## How to use
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```Python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("nghuyong/ernie-2.0-base-en")
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model = AutoModel.from_pretrained("nghuyong/ernie-2.0-base-en")
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```
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## Citation
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config.json
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{
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"attention_probs_dropout_prob": 0.1,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"max_position_embeddings": 512,
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"sent_type_vocab_size": 4,
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"task_type_vocab_size": 16,
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"vocab_size": 30522,
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"layer_norm_eps": 1e-05,
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"model_type": "bert",
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"architectures": [
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"BertModel"
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],
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"type_vocab_size": 4,
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"intermediate_size": 3072
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}
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flax_model.msgpack
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pytorch_model.bin
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tf_model.h5
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