Yueqian LinandSy0307
e788ef6e76
Signed-off-by: Yueqian Lin <linyueqian@outlook.com> Signed-off-by: Sy0307 <24841857+Sy0307@users.noreply.github.com> Co-authored-by: Sy0307 <24841857+Sy0307@users.noreply.github.com>
63 lines
2.0 KiB
Python
63 lines
2.0 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Configuration for the PersonaPlex Helium temporal transformer."""
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from __future__ import annotations
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from typing import Any
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from transformers import PretrainedConfig
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__all__ = ["HeliumConfig"]
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class HeliumConfig(PretrainedConfig):
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"""Minimal HF config for the Moshi temporal LM backbone.
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The defaults are measured from the PersonaPlex checkpoint rather than inferred
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from Moshi's higher-level kwargs.
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"""
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model_type = "helium"
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keys_to_ignore_at_inference = ("past_key_values",)
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def __init__(
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self,
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hidden_size: int = 4096,
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num_hidden_layers: int = 32,
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num_attention_heads: int = 32,
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head_dim: int = 128,
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num_key_value_heads: int = 32,
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intermediate_size: int = 11264,
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max_position_embeddings: int = 3000,
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rope_theta: float = 10000.0,
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rms_norm_eps: float = 1e-8,
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vocab_size: int = 32000,
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sliding_window: int = 3000,
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hidden_act: str = "silu",
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attention_bias: bool = False,
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mlp_bias: bool = False,
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tie_word_embeddings: bool = False,
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use_cache: bool = True,
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**kwargs: Any,
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) -> None:
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super().__init__(
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tie_word_embeddings=tie_word_embeddings,
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**kwargs,
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)
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self.hidden_size = hidden_size
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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.head_dim = head_dim
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self.num_key_value_heads = num_key_value_heads
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self.intermediate_size = intermediate_size
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self.max_position_embeddings = max_position_embeddings
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self.rope_theta = rope_theta
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self.rms_norm_eps = rms_norm_eps
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self.vocab_size = vocab_size
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self.sliding_window = sliding_window
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self.hidden_act = hidden_act
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self.attention_bias = attention_bias
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self.mlp_bias = mlp_bias
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self.use_cache = use_cache
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