| """Helion model configuration.""" |
|
|
| from transformers.configuration_utils import PretrainedConfig |
| from transformers.utils import logging |
|
|
| logger = logging.get_logger(__name__) |
|
|
|
|
| class HelionConfig(PretrainedConfig): |
| """ |
| Configuration class for Helion model. |
| |
| Args: |
| vocab_size (int, optional): Vocabulary size. Defaults to 32768. |
| hidden_size (int, optional): Dimensionality of hidden layers. Defaults to 4096. |
| intermediate_size (int, optional): Dimensionality of MLP. Defaults to 14336. |
| num_hidden_layers (int, optional): Number of decoder layers. Defaults to 32. |
| num_attention_heads (int, optional): Number of attention heads. Defaults to 32. |
| num_key_value_heads (int, optional): Number of key-value heads for GQA. Defaults to 8. |
| hidden_act (str, optional): Activation function. Defaults to "silu". |
| max_position_embeddings (int, optional): Maximum sequence length. Defaults to 8192. |
| initializer_range (float, optional): Standard deviation for weight initialization. Defaults to 0.02. |
| rms_norm_eps (float, optional): Epsilon for RMS normalization. Defaults to 1e-6. |
| use_cache (bool, optional): Whether to use KV cache. Defaults to True. |
| pad_token_id (int, optional): Padding token ID. Defaults to None. |
| bos_token_id (int, optional): Beginning of sequence token ID. Defaults to 1. |
| eos_token_id (int, optional): End of sequence token ID. Defaults to 2. |
| tie_word_embeddings (bool, optional): Tie input/output embeddings. Defaults to False. |
| rope_theta (float, optional): Base for RoPE. Defaults to 10000.0. |
| rope_scaling (dict, optional): RoPE scaling config. Defaults to None. |
| attention_bias (bool, optional): Add bias to attention projections. Defaults to False. |
| attention_dropout (float, optional): Dropout for attention. Defaults to 0.0. |
| mlp_bias (bool, optional): Add bias to MLP. Defaults to False. |
| """ |
| |
| model_type = "helion" |
| keys_to_ignore_at_inference = ["past_key_values"] |
| |
| def __init__( |
| self, |
| vocab_size=32768, |
| hidden_size=4096, |
| intermediate_size=14336, |
| num_hidden_layers=32, |
| num_attention_heads=32, |
| num_key_value_heads=8, |
| hidden_act="silu", |
| max_position_embeddings=8192, |
| initializer_range=0.02, |
| rms_norm_eps=1e-6, |
| use_cache=True, |
| pad_token_id=None, |
| bos_token_id=1, |
| eos_token_id=2, |
| tie_word_embeddings=False, |
| rope_theta=10000.0, |
| rope_scaling=None, |
| attention_bias=False, |
| attention_dropout=0.0, |
| mlp_bias=False, |
| residual_dropout=0.0, |
| embedding_dropout=0.0, |
| use_sliding_window=False, |
| sliding_window=None, |
| use_flash_attention_2=True, |
| pretraining_tp=1, |
| **kwargs, |
| ): |
| self.vocab_size = vocab_size |
| self.max_position_embeddings = max_position_embeddings |
| self.hidden_size = hidden_size |
| self.intermediate_size = intermediate_size |
| self.num_hidden_layers = num_hidden_layers |
| self.num_attention_heads = num_attention_heads |
| |
| |
| if num_key_value_heads is None: |
| num_key_value_heads = num_attention_heads |
| self.num_key_value_heads = num_key_value_heads |
| |
| self.hidden_act = hidden_act |
| self.initializer_range = initializer_range |
| self.rms_norm_eps = rms_norm_eps |
| self.use_cache = use_cache |
| self.rope_theta = rope_theta |
| self.rope_scaling = rope_scaling |
| self.attention_bias = attention_bias |
| self.attention_dropout = attention_dropout |
| self.mlp_bias = mlp_bias |
| self.residual_dropout = residual_dropout |
| self.embedding_dropout = embedding_dropout |
| self.use_sliding_window = use_sliding_window |
| self.sliding_window = sliding_window |
| self.use_flash_attention_2 = use_flash_attention_2 |
| self.pretraining_tp = pretraining_tp |
| |
| super().__init__( |
| pad_token_id=pad_token_id, |
| bos_token_id=bos_token_id, |
| eos_token_id=eos_token_id, |
| tie_word_embeddings=tie_word_embeddings, |
| **kwargs, |
| ) |
