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