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chinese_roberta_L-2_H-128

Fill-Mask Transformers PyTorch TensorFlow JAX
Chinese bert Inference Endpoints
Model card Files Community
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@@ -20,7 +20,7 @@ You can download the 24 Chinese RoBERTa miniatures either from the [UER-py Model
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  | | H=128 | H=256 | H=512 | H=768 |
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  | -------- | :-----------------------: | :-----------------------: | :-------------------------: | :-------------------------: |
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- | **L=2** | [**2/128 (Tiny)**][2_128] | [2/256][2_256] | [2/512][2_512] | [2/768][2_768] |
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  | **L=4** | [4/128][4_128] | [**4/256 (Mini)**][4_256] | [**4/512 (Small)**][4_512] | [4/768][4_768] |
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  | **L=6** | [6/128][6_128] | [6/256][6_256] | [6/512][6_512] | [6/768][6_768] |
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  | **L=8** | [8/128][8_128] | [8/256][8_256] | [**8/512 (Medium)**][8_512] | [8/768][8_768] |
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  | | H=128 | H=256 | H=512 | H=768 |
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  | -------- | :-----------------------: | :-----------------------: | :-------------------------: | :-------------------------: |
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+ | **L=2** | [**2/128 (Tiny)**](2_128) | [2/256][2_256] | [2/512][2_512] | [2/768][2_768] |
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  | **L=4** | [4/128][4_128] | [**4/256 (Mini)**][4_256] | [**4/512 (Small)**][4_512] | [4/768][4_768] |
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  | **L=6** | [6/128][6_128] | [6/256][6_256] | [6/512][6_512] | [6/768][6_768] |
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  | **L=8** | [8/128][8_128] | [8/256][8_256] | [**8/512 (Medium)**][8_512] | [8/768][8_768] |