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from transformers import PretrainedConfig |
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class OBIConfig(PretrainedConfig): |
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def __init__(self, |
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model_type="OBILanguageModel", |
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auto_map={ |
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"AutoConfig": "modelConfig.OBIConfig", |
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"AutoModel": "modelLM.OBILanguageModel", |
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"AutoModelForCausalLM": "modelLM.OBILanguageModel", |
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"AutoModelForQuestionAnswering": "modelLM.OBILanguageModel" |
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}, |
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vocab_size=1000, |
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hidden_size=4, |
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num_attention_heads=2, |
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num_hidden_layers=2, |
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hidden_dropout_prob=0.1, |
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block_size=100, |
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batch_size=60, |
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max_iters=200, |
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eval_interval=100, |
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learning_rate=0.001, |
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device="cpu", |
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**kwargs |
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)->None: |
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super().__init__(**kwargs) |
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self.model_type = model_type |
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self.auto_map = auto_map |
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self.vocab_size = vocab_size |
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self.hidden_size = hidden_size |
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self.num_attention_heads = num_attention_heads |
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self.num_hidden_layers = num_hidden_layers |
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self.hidden_dropout_prob = hidden_dropout_prob |
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self.block_size = block_size |
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self.batch_size = batch_size |
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self.max_iters = max_iters |
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self.eval_interval = eval_interval |
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self.learning_rate = learning_rate |
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self.device = device |
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