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from transformers import CamembertConfig
class CLIPTextCamembertConfig(CamembertConfig):
# ref : https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased/blob/main/config.json
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",
}
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