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cb41b16 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | """HuggingFace Transformers config for ExpIvme-DiffusionConversate-v1-Instruct."""
from transformers import PretrainedConfig
class ExpIvmeDiffusionConfig(PretrainedConfig):
model_type = "expivme_diffusion"
def __init__(self, vocab_size=16004, hidden_dim=896, n_layers=12, n_heads=14,
context_len=1024, ffn_mult=4.0, rope_theta=10_000.0, norm_eps=1e-5,
tie_embeddings=True, dropout=0.0, mask_token_id=16000,
user_token_id=16001, assistant_token_id=16002, endturn_token_id=16003, **kwargs):
self.vocab_size = vocab_size
self.hidden_dim = hidden_dim
self.n_layers = n_layers
self.n_heads = n_heads
self.context_len = context_len
self.ffn_mult = ffn_mult
self.rope_theta = rope_theta
self.norm_eps = norm_eps
self.dropout = dropout
self.mask_token_id = mask_token_id
self.user_token_id = user_token_id
self.assistant_token_id = assistant_token_id
self.endturn_token_id = endturn_token_id
self.max_position_embeddings = context_len
self.num_hidden_layers = n_layers
self.num_attention_heads = n_heads
self.hidden_size = hidden_dim
kwargs.setdefault("tie_word_embeddings", tie_embeddings)
super().__init__(**kwargs)
@property
def head_dim(self):
return self.hidden_dim // self.n_heads
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