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"""gLM2 model configuration""" |
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from typing import Optional |
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from transformers import PretrainedConfig |
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from transformers.utils import logging |
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logger = logging.get_logger(__name__) |
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class gLM2Config(PretrainedConfig): |
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model_type = "gLM2" |
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def __init__( |
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self, |
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dim: int = 640, |
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depth: int = 30, |
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heads: int = 10, |
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vocab_size: int = 37, |
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swiglu_multiple_of: int = 256, |
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ffn_dim_multiplier: Optional[float] = None, |
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norm_eps: float = 1e-5, |
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**kwargs |
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): |
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super().__init__(**kwargs) |
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self.dim = dim |
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self.depth = depth |
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self.heads = heads |
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self.vocab_size = vocab_size |
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self.swiglu_multiple_of = swiglu_multiple_of |
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self.ffn_dim_multiplier = ffn_dim_multiplier |
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self.norm_eps = norm_eps |
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self.auto_map = { |
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"AutoConfig": "configuration_glm2.gLM2Config", |
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"AutoModel": "modeling_glm2.gLM2Model", |
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"AutoModelForMaskedLM": "modeling_glm2.gLM2ForMaskedLM" |
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} |
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