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