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| from transformers import LlamaForCausalLM, LlamaTokenizer | |
| from transformers import LlamaModel, LlamaConfig | |
| import torch.nn as nn | |
| CODELLAMA_VOCAB_SIZE = 32016 | |
| class CodeLlamaForCausalLM(LlamaForCausalLM): | |
| _tied_weights_keys = ["lm_head.weight"] | |
| def __init__(self, config): | |
| super().__init__(config) | |
| self.model = LlamaModel(config) | |
| self.vocab_size = config.vocab_size | |
| self.lm_head = nn.Linear(config.hidden_size, CODELLAMA_VOCAB_SIZE, bias=False) | |
| self.model.embed_tokens = nn.Embedding( | |
| CODELLAMA_VOCAB_SIZE, config.hidden_size, config.pad_token_id | |
| ) | |
| # Initialize weights and apply final processing | |
| self.post_init() | |