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from transformers import CamembertConfig |
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class CLIPTextCamembertConfig(CamembertConfig): |
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model_type = "clip_text_camembert" |
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def __init__( |
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self, |
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vocab_size=25005, |
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hidden_size=768, |
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intermediate_size=3072, |
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projection_dim=512, |
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num_hidden_layers=12, |
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num_attention_heads=12, |
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max_position_embeddings=512, |
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hidden_act="gelu", |
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layer_norm_eps=1e-12, |
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attention_dropout=0.1, |
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initializer_range=0.02, |
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initializer_factor=1.0, |
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pad_token_id=1, |
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bos_token_id=0, |
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eos_token_id=2, |
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type_vocab_size=1, |
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**kwargs, |
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): |
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super().__init__( |
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pad_token_id=pad_token_id, |
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bos_token_id=bos_token_id, |
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eos_token_id=eos_token_id, |
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**kwargs, |
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) |
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self.vocab_size = vocab_size |
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self.hidden_size = hidden_size |
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self.intermediate_size = intermediate_size |
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self.projection_dim = projection_dim |
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self.num_hidden_layers = num_hidden_layers |
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self.num_attention_heads = num_attention_heads |
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self.max_position_embeddings = max_position_embeddings |
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self.layer_norm_eps = layer_norm_eps |
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self.hidden_act = hidden_act |
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self.initializer_range = initializer_range |
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self.initializer_factor = initializer_factor |
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self.attention_dropout = attention_dropout |
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self.type_vocab_size = type_vocab_size |
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self.auto_map = { |
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"AutoConfig": "configuration_clip_camembert.CLIPTextCamembertConfig", |
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"AutoModel": "modeling_clip_camembert.CLIPTextCamembertModelWithProjection", |
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} |
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