| 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 | |